Patent Publication Number: US-2009238434-A1

Title: Method for reproducing the spatial orientation of an immobilized subject in a multi-modal imaging system

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     Priority is claimed from the following commonly assigned, copending U.S. patent applications, each of which is incorporated by reference into this specification: 
     U.S. Provisional Ser. No. 61/038,789 filed Mar. 24, 2008 by Feke, entitled METHOD AND APPARATUS FOR REPRODUCING THE SPATIAL ORIENTATION OF AN IMMOBILIZED SUBJECT IN A MULTI-MODAL IMAGING SYSTEM; and 
     U.S. Provisional Ser. No. 61/094,997 filed Sep. 8, 2008 by Feke et al., entitled METHOD AND APPARATUS FOR REPRODUCING THE SPATIAL ORIENTATION OF AN IMMOBILIZED SUBJECT IN A MULTI-MODAL IMAGING SYSTEM. 
     This application is a Continuation-In-Part of the following commonly assigned, copending U.S. patent applications, each of which also is incorporated by reference into this specification: 
     U.S. Ser. No. 11/221,530 filed Sep. 9, 2005 by Vizard et al., entitled APPARATUS AND METHOD FOR MULTI-MODAL IMAGING; 
     U.S. Ser. No. 12/196,300 filed Aug. 22, 2008 by Harder et al., entitled APPARATUS AND METHOD FOR MULTI-MODAL IMAGING USING NANOPARTICLE MULTI-MODAL IMAGING PROBES; and 
     U.S. Ser. No. 12/354,830 filed Jan. 16, 2009 by Feke et al., entitled APPARATUS AND METHOD FOR MULTI-MODAL IMAGING. 
    
    
     FIELD OF THE INVENTION 
     The invention relates generally to the field of imaging systems, and more particularly to multi-modal imaging of living subjects. More specifically, the invention relates to (A) adjusting the physical, spatial orientation of an immobilized subject in a multi-modal imaging system so as substantially to reproduce or match the physical, spatial orientation of a reference subject, wherein the reference subject is either (a) the same or (b) a different subject, either (1) during a prior imaging session for a later imaging session, or, in the case where a plurality of subjects is imaged in one imaging session, (2) during a contemporaneous imaging session; and (B) adjusting the virtual, spatial orientation of an immobilized subject in a set of multi-modal images. 
     BACKGROUND OF THE INVENTION 
     Electronic imaging systems are well known for enabling molecular imaging. An exemplary electronic imaging system  10 , shown in  FIG. 1  and diagrammatically illustrated in  FIG. 2 , is the KODAK Image Station 200MM Multi-modal Imaging System. System  10  includes a light source  12 , an optical compartment  14  which can include a mirror  16 , a lens and camera system  18 , and a communication and computer control system  20  which can include a display device  22 , for example, a computer monitor. Lens and camera system  18  can include an emission filter wheel for fluorescent imaging. Light source  12  can include an excitation filter selector for fluorescent excitation or bright field color imaging. In operation, an image of an object is captured using lens and camera system  18 . System  18  converts the light image into an electronic image, which can be digitized. The digitized image can be displayed on the display device, stored in memory, transmitted to a remote location, processed to enhance the image, and/or used to print a permanent copy of the image. 
     A system for creating a tomographic image is disclosed in U.S. Patent Application Publication 2007/0238957 by Yared. A system is disclosed by Yared that includes an X-ray source, an X-ray detector, a light source, and a light detector, wherein these components are radially disposed about an imaging chamber. More specifically these components are mounted on a gantry that is rotatable about the imaging chamber. The system includes code comprising instructions to create a three dimensional optical absorption map of a target volume based at least in part on the detected X-ray radiation and to use in the optical absorption map in optical tomographic reconstruction to create the tomographic image. In addition or alternatively, Yared&#39;s system includes code comprising instructions to create a surface model of at least a portion of the object based at least in part on the detected X-ray radiation and to use the surface model in optical tomographic reconstruction to create the tomographic image. The system further may include code comprising instructions to create a three-dimensional anatomical data set using the detected X-ray radiation and to register the anatomical data set with the tomographic image to create a composite image. 
     U.S. Pat. No. 6,868,172 (Boland et al) is directed to a method for registering images in radiography applications. 
     SUMMARY OF THE INVENTION 
     The present invention provides an improved, simpler solution for combining anatomical imaging with molecular imaging. The invention does not require a complex tomographic imaging system, nor radial disposition of an X-ray source, an X-ray detector, a light source, and a light detector about an imaging chamber, nor mounting of these components on a gantry rotatable about the imaging chamber. Furthermore, the present invention typically is not necessary for tomographic imaging systems wherein the spatial orientation of the subject does not affect the resulting data since in tomography the spatial orientation is not projected into a two-dimensional planar representation but instead may float in a three-dimensional representation. However, the technical features of the invention relating to a region of interest template would be useful in a tomographic system for longitudinal studies or sequentially different subject studies, in which case the region of interest would the three-dimensional. In comparison, the present invention is advantageous for planar imaging systems because in such systems the spatial orientation, such as the cranio-caudal rotation angle of the subject, may affect the resulting data. Furthermore, the present invention is more generally applied to all modes of molecular imaging, including optical imaging and imaging of ionizing radiation, such as from radio-isotopic probes, by means of a phosphor screen. 
     Applicants have recognized a need for substantially reproducing the spatial orientation of an immobilized subject, such as a small animal, in a multi-modal imaging system used to take time-spaced images of the subject. For example, in known imaging methods a small animal used in a longitudinal multi-modal molecular imaging study typically has been loaded into an animal chamber, such as a right circular cylindrical tube, for a first time and imaged for the first time. The animal then is unloaded from the animal chamber, later loaded back into the animal chamber for at least a second time, and imaged for at least the second time. Thus, a first-time set of multi-modal molecular images and at least a second-time set of multi-modal molecular images are provided. If the physical, spatial orientation of the animal, for example the cranio-caudal rotation angle of the animal, with respect to the tube and/or the imaging system is different between the first time and the at least second time, then the at least second-time set of multi-modal molecular images may be affected by the difference in the physical, spatial orientation compared to the first-time set of multi-modal molecular images. This difference may result in artifacts, such as relative attenuation or enhancement of a molecular signal, upon comparison to the first-time set of multi-modal molecular images. 
       FIG. 33A  illustrates an example of relative attenuation or enhancement of fluorescence molecular signals for different cranio-caudal rotation angles, typical for known methods. A graph of the fluorescence intensity vs. cranio-caudal rotation angle is provided for several organs in the body of a mouse, including the bladder, kidney, stomach, and intestines.  FIG. 33B  illustrates an example of relative attenuation or enhancement of radio-isotopic molecular signals for different cranio-caudal rotation angles, also typical for known methods. A graph of radio-isotopic signal vs. cranio-caudal rotation angle is provided for simulated radionuclide-labeled tissue in the body of a mouse. Continuing with regard to the example of the known method described above, if the physical, spatial orientation of the animal is different between the first time and the at least second time, then the first-time set of multi-modal molecular images and the at least second-time set of multi-modal molecular images cannot be precisely co-registered. Lack of co-registration can degrade the quantitation provided by a simple regions-of-interest analysis wherein a single regions-of-interest template is applied to both the first-time set of multi-modal molecular images and the at least second-time set of multi-modal molecular images. Similar problems arise with known methods when a plurality of animals is loaded serially into a field of view. 
     For example, when a plurality of small animals is used in known methods for a multi-modal molecular imaging study, the animals are loaded into animal chambers, such as right circular cylindrical tubes, whereby the loading may be performed serially at a given spatial location within the field of view of the multi-modal imaging system, or may be performed in parallel across a plurality of spatial locations in the field of view of the multi-modal imaging system. In such an example, the physical, spatial orientations of the animals, for example the cranio-caudal rotation angles, may differ among the plurality of animals. As a result, each set of multi-modal molecular images for each animal may be affected by the difference in the physical, spatial orientation, thereby resulting in artifacts, such as relative attenuation or enhancement of a molecular signal, in one set of multi-modal molecular images compared to another set of multi-modal molecular images. 
     If small animals are loaded in parallel across a plurality of spatial locations in the field of view in known methods of using the multi-modal imaging system, then regions of interest defined for one animal may not be spatially translatable to the other animals by the simple difference between the spatial locations of the animals due to differences in the physical, spatial orientations, for example the cranio-caudal rotation angles, of the animals at their locations. As a result, degraded quantitation may be provided by a simple regions-of-interest analysis wherein an array-like regions-of-interest template (i.e., multiple copies of a set of regions of interest across the field of view) is applied to the set of multi-modal molecular images. 
     The problems of known methods caused by different physical, spatial orientations of test animals during different imaging sessions are solved or substantially reduced by implementation of the method and apparatus of the present invention. 
     A first embodiment of the inventive method substantially reproduces the physical, spatial orientation of an immobilized subject in an X-ray imaging system including a computer, from a prior imaging session for a later imaging session. The method includes steps of: performing a physical, spatial orientation of the immobilized subject for a first time in the imaging system; using the computer, acquiring an X-ray anatomical image of the immobilized subject for the first time in the imaging system; performing a test physical, spatial orientation of the immobilized subject for a next time in the imaging system; using the computer, acquiring a test X-ray anatomical image of the immobilized subject for the next time in the imaging system; using the computer, comparing the test X-ray anatomical image for the next time and the X-ray anatomical image for the first time, including a calculation of the difference therebetween; physically, spatially reorienting the immobilized subject to improve the comparison, if the comparison is not satisfactory to demonstrate reproduction of the physical, spatial orientation for the first time; repeating the steps of performing a test physical, spatial orientation, acquiring a test X-ray anatomical image, comparing the test X-ray anatomical image and physically, spatially reorienting the immobilized subject until the comparison is satisfied; and using the computer, acquiring an X-ray anatomical image of the immobilized subject for the next time in the multi-modal imaging system. 
     A second embodiment of the inventive method reproduces the physical, spatial orientation of an immobilized subject in an X-ray imaging system including a computer from one subject for another subject. The method includes steps of: performing a physical, spatial orientation of a first immobilized subject in the multi-modal imaging system, using the computer, acquiring an X-ray anatomical image of the first immobilized subject in the imaging system; performing a physical, spatial orientation of a next immobilized subject in the imaging system; using the computer, acquiring a test X-ray anatomical image of the next immobilized subject in the imaging system; using the computer, comparing the test X-ray anatomical image of the next immobilized subject and the X-ray anatomical image of the first immobilized subject, including a calculation of the difference therebetween; physically, spatially reorienting the next immobilized subject to improve the comparison, if the comparison is not satisfactory to demonstrate reproduction of the physical, spatial orientation of the first immobilized subject; repeating the steps of performing a physical, spatial orientation of a next immobilized subject, acquiring a test X-ray anatomical image, comparing and physically, spatially reorienting until the comparison is satisfied; and acquiring an X-ray anatomical image of the next immobilized subject in the multi-modal imaging system. 
     A third embodiment of the inventive method reproduces the physical, spatial orientation of a plurality of immobilized subjects in an X-ray imaging system including a computer. The method includes steps of: performing a test physical, spatial orientation of the plurality of immobilized subjects in the imaging system; using the computer, acquiring a test X-ray anatomical image of the plurality of immobilized subjects in the imaging system; using the computer, dividing the test X-ray anatomical image of the plurality of immobilized subjects into X-ray anatomical image sections corresponding to each subject; using the computer, comparing the test X-ray anatomical image section corresponding to each subject to the test X-ray anatomical image section of a reference subject selected from the test X-ray anatomical images of the plurality of immobilized subjects, including a calculation of the difference between X-ray anatomical image sections; physically, spatially reorienting each immobilized subject, except the reference subject to improve the comparison, if the comparison is not satisfactory to demonstrate reproduction of the reference subject; repeating the steps of performing, acquiring, dividing, comparing and physically, spatially reorienting until comparison is satisfied; and using the computer, acquiring an X-ray anatomical image of the plurality of immobilized subjects in the multi-modal-imaging system. 
     A fourth embodiment of the inventive method registers and analyzes multi-modal molecular images of an immobilized subject in a multi-modal imaging system including a computer, for a plurality of times. The method includes steps of; performing a physical, spatial orientation of the immobilized subject for a first time in the multi-modal imaging system; using the computer, acquiring an X-ray anatomical image of the immobilized subject for the first time in the multi-modal imaging system; using the computer, acquiring a set of multi-modal molecular images of the immobilized subject for the first time using a set of modes of the multi-modal imaging system, wherein the set of multi-modal molecular images may include at least one image acquired using at least one mode included in the set of modes; using the computer, creating regions-of-interest templates identifying the regions of interest in the set of multi-modal molecular images for the first time; using the computer, applying the regions-of-interest templates to measure the molecular signals in the regions of interest in the set of multi-modal molecular images of the immobilized subject for the first time; using the computer, acquiring an X-ray anatomical image of the immobilized subject for a next time in the multi-modal imaging system; using the computer, acquiring a set of multi-modal molecular images of the immobilized subject for the next time using a set of modes of the multi-modal imaging system, wherein the set of multi-modal molecular images may include at least one image acquired using at least one mode included in the set of modes; using the computer, comparing the X-ray anatomical image for the next time and the X-ray anatomical image for the first time, including a calculation of the difference between; using the computer, registering the X-ray anatomical image for the next time to the X-ray anatomical image for the first time by virtually, spatially reorienting the X-ray anatomical image for the next time to improve the comparison, if the comparison is not satisfactory to demonstrate registration to the X-ray anatomical image for the first time; using the computer, registering the set of multi-modal molecular images for the next time to the set of multi-modal molecular images for the first time, by applying the same spatial transformation parameters as were applied to the X-ray anatomical image for the next time to the set of multi-modal molecular images for the next time; and using the computer, applying the regions-of-interest templates to measure the molecular signals in the regions of interest in the set of multi-modal molecular images of the immobilized subject for the next time. 
     A fifth embodiment of the inventive method reproduces the physical, spatial orientation of one or more immobilized subjects in an X-ray imaging system including a computer. The method includes steps of: performing a reference series of physical, spatial orientations of the immobilized subject(s) in the imaging system; using the computer, acquiring a reference X-ray anatomical image of each subject for each physical, spatial orientation of the reference series; using the computer, using the reference X-ray anatomical images to calculate a first plurality of correspondences for achieving desired physical, spatial orientations of the subjects of the reference series for X-ray images; performing a test series of physical, spatial orientations of immobilized subject(s) in the imaging system; using the computer, acquiring a test X-ray anatomical image of the immobilized subject(s) for each physical, spatial orientation of the test series; and using the computer, using the test X-ray anatomical images to calculate a second plurality of correspondences for selecting reproduced desired physical, spatial orientations of the subjects of the test series for X-ray images. 
     A sixth embodiment of the inventive method adjusts a physical, spatial orientation of at least one immobilized subject in an X-ray imaging system including a computer, so as substantially to reproduce the physical, spatial orientation of another, reference immobilized subject. The method includes steps of: performing a physical, spatial orientation of the reference subject; using the computer, acquiring an X-ray anatomical image of the reference subject; performing a physical, spatial orientation of the at least one subject; using the computer, acquiring an X-ray anatomical image of the at least one subject; using the computer, analyzing the combination of the X-ray anatomical image of the reference subject and the X-ray anatomical image of the at least one subject; and following the analyzing, physically, spatially reorienting the at least one subject so as substantially to reproduce the physical, spatial orientation of the reference subject. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The foregoing and other objects, features, and advantages of the invention will be apparent from the following more particular description of the embodiments of the invention, as illustrated in the accompanying drawings. The elements of the drawings are not necessarily to scale relative to each other. 
         FIG. 1  shows a perspective view of an exemplary electronic imaging system. 
         FIG. 2  shows a diagrammatic view of the electronic imaging system of  FIG. 1 . 
         FIG. 3A  shows a diagrammatic side view of an imaging system useful in accordance with the present invention. 
         FIG. 3B  shows a diagrammatic front view of the imaging system of  FIG. 3A . 
         FIG. 4  shows a perspective view of the imaging system of  FIGS. 3A and 3B . 
         FIG. 5A  shows a diagrammatic partial view of a mouse in a sample chamber on a sample object stage of the imaging system of  FIGS. 3A and 3B  when either (a) a first-time X-ray anatomical image is acquired in accordance with the present invention, or (b) a next-time X-ray anatomical image is virtually, spatially reoriented in accordance with the invention. 
         FIG. 5B  shows a diagrammatic partial view of the mouse in the sample chamber on the sample object stage of the imaging system of  FIGS. 3A and 3B  when a first-time set of multi-modal molecular images is acquired in accordance with the present invention. 
         FIG. 6  shows a workflow diagram in accordance with a method of the present invention. 
         FIG. 7A  shows a diagrammatic partial view of the mouse in the sample chamber on the sample object stage of the imaging system of  FIGS. 3A and 3B  when a next-time test X-ray anatomical image is acquired in accordance with the present invention. 
         FIG. 7B  shows a diagrammatic partial view of the mouse in the sample chamber on the sample object stage of the imaging system of  FIGS. 3A and 3B  when a next-time X-ray anatomical image after physical, spatial reorientation is acquired in accordance with the present invention. 
         FIG. 7C  shows a diagrammatic partial view of the mouse in the sample chamber on the sample object stage of the imaging system of  FIGS. 3A and 3B  when a next-time set of multi-modal molecular images (a) is acquired in accordance with the present invention or (b) has been virtually, spatially reoriented in accordance with the present invention. 
         FIG. 8  shows a workflow diagram in accordance with a method of the present invention. 
         FIG. 9  shows a flow diagram of statistical method used in step  260  of  FIG. 8  in accordance with the present invention. 
         FIG. 10  shows a flow diagram of another embodiment of a method used in step  260  of  FIG. 8  in accordance with the present invention. 
         FIG. 11  shows a diagrammatic partial view of a plurality of subject mice in a corresponding plurality of sample chambers on the sample object stage of the imaging system of  FIGS. 3A and 3B  being imaged serially in accordance with the present invention. 
         FIG. 12  shows a workflow diagram in accordance with a method of the present invention. 
         FIG. 13  shows a workflow diagram in accordance with a method of the present invention. 
         FIG. 14  shows a flow diagram of statistical method used in step  660  of  FIG. 13  in accordance with the present invention. 
         FIG. 15  shows a flow diagram of another embodiment of a method used in step  660  of  FIG. 13  in accordance with the present invention. 
         FIG. 16  shows a diagrammatic partial view of a plurality of subject mice in a corresponding plurality of sample chambers on the sample object stage of the imaging system of  FIGS. 3A and 3B  being imaged in parallel in accordance with the present invention. 
         FIG. 17  shows several multi-subject images acquired in accordance with the present invention. 
         FIG. 18  shows a workflow diagram in accordance with a method of the present invention. 
         FIG. 19  shows a flow diagram of statistical method used in step  1030  of  FIG. 18  in accordance with the present invention. 
         FIG. 20  shows a flow diagram of another embodiment of a method used in step  1030  of  FIG. 18  in accordance with the present invention. 
         FIG. 21  is a graphical representation of the first-time molecular signals measured in regions of interest in accordance with the present invention. 
         FIG. 22  shows a workflow diagram in accordance with a method of the present invention. 
         FIG. 23  is a graphical representation of the next-time molecular signals measured in regions of interest in accordance with the present invention. 
         FIG. 24  is a graphical representation of the next-time molecular signals measured in regions of interest from a virtually, spatially reoriented image in accordance with the present invention. 
         FIG. 25  shows a workflow diagram in accordance with a method of the present invention. 
         FIG. 26  shows a flow diagram of statistical method used in step  3320  of  FIG. 31  in accordance with the present invention. 
         FIG. 27  shows a flow diagram of another embodiment of a method used in step  3320  of  FIG. 25  in accordance with the present invention. 
         FIG. 28  shows use of an exogenous X-ray anatomical image contrast agent to provide contrast with soft tissue. 
         FIG. 29  shows use of an exogenous X-ray anatomical image contrast device to provide contrast with soft tissue. 
         FIG. 30  shows an alternative flow diagram of statistical method used in step  260  of  FIG. 8  in accordance with the present invention. 
         FIG. 31  shows an alternative flow diagram of statistical method used in step  660  of  FIG. 13  in accordance with the present invention; and 
         FIG. 32  shows an alternative flow diagram of statistical method used in step  1030  of  FIG. 18  in accordance with the present invention. 
         FIG. 33A  shows a graph of fluorescence intensity vs. cranio-caudal rotation angle for several organs in the body of a mouse. 
         FIG. 33B  shows a graph of radio-isotopic signal vs. cranio-caudal rotation angle for simulated radionuclide-labeled tissue in the body of a mouse. 
         FIG. 34  shows a series of reference X-ray images of a mouse incrementally rotated through various cranio-caudal rotation angles. 
         FIG. 35A  shows the series of reference X-ray images of a mouse of  FIG. 34  with a gradient filter in applied, and the location of line profiles. 
         FIG. 35B  shows the series of reference X-ray images of a mouse of  FIG. 34  with a different gradient filter applied which is opposite the gradient filter applied in  FIG. 35A , and the location of line profiles. 
         FIG. 36  shows line profiles of the series of images shown in  FIGS. 35A  and B, wherein the abscissae of the line profiles of the series of images from  FIG. 35B  have been reversed. 
         FIG. 37  shows a graph of the maximum of the cross-correlation of the line profiles shown in  FIG. 36  vs. cranio-caudal rotation angle. 
         FIG. 38A  shows the series of test X-ray images of a mouse of  FIG. 34 , shifted one image to the right, with a gradient filter in applied, and the location of line profiles. 
         FIG. 38B  shows the series of test X-ray images of a mouse of  FIG. 34 , shifted one image to the right, with a different gradient filter applied which is opposite the gradient filter applied in  FIG. 38A , and the location of line profiles. 
         FIG. 39  shows line profiles of the series of images shown in  FIGS. 3845A  and B, wherein the abscissae of the line profiles of the series of images from  FIG. 38B  have been reversed. 
         FIG. 40  shows a graph of the maximum of the cross-correlation of the line profiles shown in  FIG. 39  vs. cranio-caudal rotation angle. 
         FIGS. 41A and 41B  show a workflow diagram in accordance with a method of the present invention. 
         FIGS. 42A and 42B  show a workflow diagram in accordance with another method of the present invention. 
         FIG. 43  shows a series of reference X-ray anatomical images of a mouse incrementally rotated through various cranio-caudal rotation angles. 
         FIG. 44  shows X-ray density images corresponding to the images of  FIG. 43 . 
         FIG. 45  shows a series of binary threshold images corresponding to the images of  FIG. 44 . 
         FIG. 46  shows a series of gradient images corresponding to the images of  FIG. 43 . 
         FIG. 47  shows the images of  FIG. 45  imagewise multiplied by the images of  FIG. 46 . 
         FIG. 48  shows the imagewise absolute value of the images of  FIG. 47 . 
         FIG. 49  shows a graph of normalized absolute values versus orientation of the subject. 
         FIGS. 50A and 50B  show a work flow diagram for producing the images of  FIGS. 43 to 49 . 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     The invention has been described in detail with particular reference to certain preferred embodiments thereof, but it will be understood that variations and modifications can be effected within the spirit and scope of the invention. The following is a detailed description of the preferred embodiments of the invention, reference being made to the drawings in which the same reference numerals identify the same elements of structure in each of the several figures. 
     Reference is made to commonly assigned, copending provisional U.S. Patent Application Ser. No. 61/131,948 filed Jun. 13, 2008 by Feke et al., and entitled TORSIONAL SUPPORT APPARATUS FOR CRANIOCAUDAL ROTATION OF ANIMALS, which is incorporated by reference into this specification. 
     As shown in  FIG. 3A , imaging system  100  includes an X-ray source  102  and a sample object stage  104 . Imaging system  100  further comprises epi-illumination, for example, using fiber optics  106 , which directs conditioned light (of appropriate wavelength and divergence) toward sample object stage  104  to provide bright-field or fluorescent imaging. Sample object stage  104  is disposed within a sample environment  108 , which allows access to the object being imaged. Preferably, a radiographic phosphor screen, not shown, is positioned between stage  104  and camera and lens system  18  to transduce projected X-rays into visible light for capture by system  18 . 
     Commonly assigned U.S. Pat. No. 6,444,988 by Vizard, entitled: ELECTRONIC IMAGING SCREEN WITH OPTICAL INTERFERENCE COATING discloses such a screen and its disclosure is incorporated by reference into this specification. 
     The screen may be movable into and out of the X-ray beam, as disclosed in the previously mentioned U.S. patent application Ser. No. 11/221,530 and 12/354,830. Preferably, sample environment  108  is light-tight and fitted with light-locked gas ports for environmental control. Such environmental control might be desirable for controlled X-ray imaging or for support of particular specimens. Environmental control enables practical X-ray contrast below 8 KeV (air absorption) and aids in life support for biological specimens. Imaging system  100  can include an access means or member  110  to provide convenient, safe and light-tight access to sample environment  108 . Access means are well known to those skilled in the art and can include a door, opening, labyrinth, and the like. Additionally, sample environment  108  is preferably adapted to provide atmospheric control for sample maintenance or soft X-ray transmission (e.g., temperature/humidity/alternative gases and the like). The inventions disclosed in the previously mentioned U.S. patent applications of Harder et al. and Vizard et al., are examples of electronic imaging systems capable of multi-modal imaging that are useful in accordance with the present invention. 
       FIGS. 5A and 5B  show diagrammatic partial views of a cylindrical sample chamber or tube  118  and a sample object stage  104  of the imaging system  100  of  FIGS. 3A and 3B . A subject mouse  112  is administered immobilizing anesthesia through a respiratory device  114  connected to an outside source via a tube  116  that enters the chamber  118  via the light-locked gas ports. A first-time X-ray anatomical image  120  of  FIG. 5A  and a first-time set of multi-modal molecular images  122  of  FIG. 5B  are acquired of the immobilized subject mouse  112 . 
     As shown in the flow chart of  FIG. 6 , a first-time physical, spatial orientation of immobilized subject  112  is performed at step  200 , followed by acquisition of first-time X-ray anatomical image  120  at step  210  and first-time set of multi-modal molecular images  122  at step  220 . A set of modes of multi-modal imaging system  100  is used at step  220 . These modes may include at least one of bright-field mode, dark-field mode, and radio isotopic mode. The first set of multi-modal molecular images may include at least one image acquired using at least one mode included in the first set of modes. First-time set of multi-modal molecular images  122  is acquired using the same camera conditions, such as zoom and focus, as the first X-ray anatomical image  120 . Thus, co-registration between image  120  and images  122  is achieved by virtue of the fact the physical, spatial orientation of subject  112  does not change between capture of images  122  and image  120 . 
     Now referring to  FIG. 7A , a next-time test X-ray anatomical image  124  is acquired of immobilized subject  112 . The next-time test X-ray anatomical image  124  may be an image taken after the subject has been removed from and then returned to chamber  118  and/or system  100 . Image  124  may be an image of subject  112  taken after a long period of time, for example 24 hours, since image  120  was captured. Or, image  124  may be taken after some occurrence has caused subject  112  to change its position hence changing its physical, spatial orientation with respect to chamber  118  and/or system  100 . 
       FIG. 7B  illustrates the acquisition a next-time X-ray anatomical image  130  of subject  112  in sample tube  118  of system  100  after physical, spatial reorientation of the subject has been performed. The physical, spatial reorientation may be performed by manual means, or robotic means controlled by the communication and computer control system  20 , for example via a rotational mechanism  126  and an X-Y translation mechanism  128  as shown in  FIGS. 5A  and B; and  7 A, B and C. 
       FIG. 7C  illustrates the acquisition a next-time set of multi-modal molecular images  132  of subject  112  in sample tube  118  of system  100  after either (a) physical, spatial reorientation or (b) virtual, spatial reorientation of the subject has been performed. 
     As shown in the workflow chart in  FIG. 8 , a next-time test physical, spatial orientation of immobilized subject  112  in system  100  is performed at step  230 , followed by acquisition of image  124  at step  240 , then comparison of image  124  to image  120  against matching criteria designed to match the next-time test physical, spatial orientation to the first-time physical, spatial orientation at step  250 . The comparison may be made by a calculation of the difference between image  124  and image  120 , or the comparison may be according to the digital image processing method for image registration described in commonly assigned U.S. Pat. No. 7,263,243 of Chen et al., the disclosure of which is incorporated by reference in this specification. The comparison may be manual or automated. The comparison may be performed based on endogenous X-ray anatomical image contrast, such as from skeletal and/or soft tissue, or exogenous X-ray anatomical image contrast, such as injected, implanted, and/or otherwise attached radio-opaque imaging agents or devices. If the analysis of the output of the comparison at step  250  is satisfactory, corresponding to the “YES” branch of step  250 , the next-time set of multi-modal molecular images  132  may be acquired in step  270 . The set of imaging modes may include at least one of bright-field mode, dark-field mode, and radio isotopic mode, and the next-time set of multi-modal molecular images  132  may include at least one image acquired using at least one mode included in the set of modes. The next-time set of multi-modal molecular images  132  may be co-registered with the next-time test X-ray anatomical image  124 , thereby resulting in the next-time set of multi-modal molecular images  132  being additionally co-registered with the first-time set of multi-modal molecular images  122  and the first-time X-ray anatomical image  120 . If the output of the comparison is unsatisfactory, corresponding to the “NO” branch of step  250 , immobilized subject  112  is physically, spatially reoriented in step  260  to improve the comparison. The physical, spatial reorientation may be determined by spatially mapping the results determined from the digital image processing method for image registration described in the previously mentioned U.S. patent of Chen et al., to the subject  112 , or the physical, spatial reorientation may be made by trial-and-error. The physical, spatial reorientation may be performed by manual means, or by robotic means controlled by the communication and computer control system  20  as previously discussed. Steps  240 ,  250 , and  260  are repeated until the output of the comparison is satisfactory, thereby corresponding to the “YES” branch of step  250 , and proceeding accordingly as described above. 
     In an embodiment the following statistical method is used for step  260  of  FIG. 8 . Referring to the workflow shown in  FIG. 9 , a physical, spatial reorientation of subject  112  to achieve a match between image  120  and image  124  is accomplished by steps of applying vector quantization to image  120  and image  124 ; converting these X-ray anatomical images to vectorized X-ray anatomical images having corresponding local intensity information as derived respectively from the X-ray anatomical images at step  300 ; obtaining a joint statistical representation of the X-ray anatomical images by employing the vectorized X-ray anatomical images at step  310 ; computing a cost function using the joint statistical representation of the X-ray anatomical images at step  320 ; selecting a reference image (the first-time X-ray anatomical image) from the plurality of X-ray anatomical images at step  330 ; and evaluating the cost function at step  340 . If the predetermined cost function criterion is unsatisfied as shown in the “NO” branch of step  340 , the subject is physically, spatially reoriented according to its virtual, spatial correspondence to the reference image at step  350 , and flow goes back to step  300  of  FIG. 9 . If the predetermined cost function criterion is satisfied as shown in the “YES” branch of step  340 , the physical, spatial reorientation is complete and the next-time set of multi-modal molecular images can be acquired at step  270  of  FIG. 8 . Persons skilled in the art understand that step  260  can be implemented with or without vector quantization in step  300 . 
     In another embodiment the following method is used for step  260  of  FIG. 8 . Referring to the workflow shown in  FIG. 30 , a physical, spatial reorientation of subject  112  to achieve a match between image  120  and image  124  is accomplished by steps of selecting a reference image (image  120 ) at step  4000 ; applying an image registration algorithm (e.g. described in the previously mentioned U.S. patent of Chen et al.) to image  120  and image  124  at step  4010 ; obtaining a minimal cost function value from the image registration process at step  4020 ; obtaining a virtual spatial displacement map corresponding to the minimal cost function from the image registration process at step  4030 ; and evaluating the cost function at step  4040 . If the predetermined cost function criterion is unsatisfied as shown in the “NO” branch of step  4040 , the subject is physically, spatially reoriented according to the virtual spatial displacement map at step  4050 , and flow goes back to step  4000  of  FIG. 30 . If the predetermined cost function criterion is satisfied as shown in the “YES” branch of step  4040 , the physical, spatial reorientation is complete and the next-time set of multi-modal molecular images can be acquired at step  270  of  FIG. 8 . The virtual spatial displacement map can be computed based on the virtual spatial transformation described by Chen et al. 
     In another embodiment the following method is used for step  260  of  FIG. 8 . Referring to the work flow shown in  FIG. 10 , image  120  is compared to image  124 ; a calculation of the image difference between the two X-ray anatomical images is made at step  400 ; and a comparison of the image difference to a null (zero) image is made at step  410 . Where the comparison of the image difference to a null (zero) image is not satisfactory as shown in the “NO” branch of step  420 , subject  112  is physically, spatially reoriented according to its virtual, spatial correspondence to the reference image at step  430 , and the flow goes back to step  400  of  FIG. 10 . If the comparison of the image difference to a null (zero) image is satisfactory as shown in “YES” branch of step  420 , the physical, spatial reorientation is complete and the next-time set of multi-modal molecular images can be acquired at step  270  of  FIG. 8 . 
     In a second embodiment of the present invention the physical, spatial reorientations of the subjects involves comparing different animals as shown in  FIG. 11 . A plurality of small animals such as subject mice  500   a, b, c , and  d  are used in a multi-modal molecular imaging study and are loaded into animal chambers, such as right circular cylindrical tubes  510   a, b, c , and  d , respectively, whereby the loading and imaging may be conducted serially. A first-subject X-ray anatomical image  520   a  of subject mouse “a” is acquired along with a first-subject set of multi-modal molecular images  530   a  using the multi-modal imaging system  100 . As previously described the acquisition of a first-subject set of multi-modal molecular images  530   a  may be made using a set of modes of system  100 . As seen in  FIG. 11 , set  530   a  includes two multi-modal molecular images, a left image  531   a  captured using a first molecular imaging mode and a right image  531   b  captured using a second molecular imaging mode. The set of modes may include at least one of bright-field mode, dark-field mode, and radio isotopic mode. The first-subject set of multi-modal molecular images  530   a  may include at least one image acquired using at least one mode included in the first set of modes. Because the first-subject set of multi-modal molecular images  530   a  is acquired using the same camera conditions, such as zoom and focus, as the first-subject X-ray anatomical image  520   a , co-registration between the first-subject X-ray anatomical image and the first-subject set of multi-modal molecular images is achieved by virtue of the fact the physical, spatial orientation does not change between capture of images  530   a  and image  520   a  for subject mouse “a”. 
     Now referring to the workflow shown in  FIG. 12 , a first-subject physical spatial orientation of an immobilized subject  500   a , subject mouse “a”, in system  100  is performed at step  600 , followed by the acquisition of a first-subject X-ray anatomical image  520   a  at step  610  and the acquisition of a first-subject set of multi-modal molecular images  530   a  of the immobilized subject  500   a  using a set of modes of the multi-modal imaging system  100  at step  620 . The set of modes may include at least one of bright-field mode, dark-field mode, and radio isotopic mode. The first set of multi-modal molecular images may include at least one image acquired using at least one mode included in the first set of modes. Because the first-subject set of multi-modal molecular images  530   a  is acquired using the same camera conditions, such as zoom and focus, as the first-subject X-ray anatomical image  520   a , co-registration between the images is achieved in the manner previously described. Referring again to  FIG. 11 , the next-subject mice  500   b, c , and  d  (subject mouse “b”, subject mouse “c”, and subject mouse “d”) are loaded serially to a plurality of next-subject physical, spatial orientations in the field of view of system  100 . A next-subject test X-ray anatomical image  525   b  c and d, respectively, is acquired for each of the next-subject mice “b”, “c”, and “d”. 
     As shown in the workflow chart in  FIG. 13 , a next-subject test physical, spatial orientation is performed for each immobilized subject mouse  500   b, c , and  d  (subject mouse “b”, subject mouse “c”, and subject mouse “d”) at step  630 , followed by acquisition of a next-subject test X-ray anatomical image  525   b, c , and  d  for each of the next-subject mice “b”, “c” and “d”, respectively, in system  100  at step  640 ; then comparison of the next-subject test X-ray anatomical image  525   b, c , and  d  to image  520   a  against matching criteria designed to match the next-subject test physical, spatial orientation to the first-subject physical, spatial orientation at step  650 . The comparison may be made by a calculation of the difference between image  525   b, c , and  d  and image  520   a , or the comparison may be according to the digital image processing method for image registration described in the U.S. patent by Chen et al. The comparison may be manual or automated. The comparison may be performed based on endogenous X-ray anatomical image contrast, such as from skeletal and/or soft tissue, or exogenous X-ray anatomical image contrast, such as injected, implanted, and/or otherwise attached radio-opaque imaging agents or devices. If the analysis of the output of the comparison at step  650  is satisfactory, corresponding to the “YES” branch of step  650 , the next-subject set of multi-modal molecular images  540   b, c , and  d  may be acquired, step  670 . As seen in  FIG. 11 , sets  540   b, c , and  d  each include two multi-modal molecular images, left images  541   a ,  542   a , and  543   a  captured using a first molecular imaging mode and right images  541   b ,  542   b , and  543   b  captured using a second molecular imaging mode. The set of modes may include at least one of bright-field mode, dark-field mode, and radio isotopic mode. The at least next-subject set of multi-modal molecular images  540   b, c , and  d  may include at least one image acquired using at least one mode included in the set of modes, and whereby the next-subject set of multi-modal molecular images  540   b, c , and  d  is co-registered with the next-subject test X-ray anatomical image  525   b, c , and  d , thereby resulting in the next-subject set of multi-modal molecular images  540   b, c , and  d  to be additionally co-registered with the first-subject set of multi-modal molecular images  530   a  and the first-subject X-ray anatomical image  520   a . If the output of the comparison is unsatisfactory, corresponding to the “NO” branch of step  650 , the immobilized subjects mice  500   b, c , and  d  are physically, spatially reoriented at step  660  to improve the comparison. The reorientation may be determined by spatially mapping the results determined from the digital image processing method for image registration described in the U.S. patent of Chen et al., to the physical subject  500   b, c , and  d , or the reorientation may be made by trial-and-error. The physical, spatial reorientation may be performed by manual means, or by robotic means controlled by the communication/computer control system  20  as previously discussed. Steps  640 ,  650 , and  660  are repeated until the output of the comparison is satisfactory, as shown by images  535   b, c  and  d  of  FIG. 11 , thereby corresponding to the “YES” branch of step  650 , and proceeding accordingly as described above. 
     In another embodiment the following statistical method is used for step  660  of  FIG. 13 . Referring to the workflow shown in  FIG. 14 , the comparison of image  520   a  to image  525   b, c , and  d  is accomplished by steps of applying vector quantization to image  520   a  and image  525   b, c , and  d ; converting these X-ray anatomical images to vectorized X-ray anatomical images having corresponding local intensity information as derived respectively from the X-ray anatomical images at step  700 ; obtaining a joint statistical representation of the X-ray anatomical images by employing the vectorized X-ray anatomical images at step  710 ; computing a cost function using the joint statistical representation of the X-ray anatomical images at step  720 ; selecting a reference image (the first-subject X-ray anatomical image) from the plurality of X-ray anatomical images at step  730 ; and evaluating the cost function at step  740 . If the predetermined cost function criterion is unsatisfied as shown in the “NO” branch of step  740 , the next subject is physically, spatially reoriented according to its virtual, spatial correspondence to the reference image at step  750 , and flow goes back to step  700  of  FIG. 14 . If the predetermined cost function criterion is satisfied as shown in the “YES” branch of step  740 , the physical, spatial reorientation is complete and the next-subject set of multi-modal molecular images can be acquired at step  670  of  FIG. 13 . Persons skilled in the art understand that step  660  can be implemented with or without vector quantization in step  700 . The spatial displacement map can be computed based on the virtual spatial transformation described by Chen et al. 
     In yet another embodiment the following method is used for step  660  of  FIG. 13 . Referring to the workflow shown in  FIG. 31 , the physical, spatial reorientation of the next subject to achieve a match between image  520   a  and image  525   b, c  and  d  is accomplished by steps of selecting a reference image (image  520   a ) at step  5000 ; applying an image registration algorithm (e.g. described in the U.S. patent of Chen et al.) to image  520  and image  525   b, c , and  d  at step  5010 ; obtaining a minimal cost function value from the image registration process at step  5020 ; obtaining a virtual spatial displacement map corresponding to the minimal cost function from the image registration process at step  5030 ; and evaluating the cost function at step  5040 . If the predetermined cost function criterion is unsatisfied as shown in the “NO” branch of step  5040 , the next subject is physically, spatially reoriented according to the virtual spatial displacement map at step  5050 , and flow goes back to step  5000  of  FIG. 31 . If the predetermined cost function criterion is satisfied as shown in the “YES” branch of step  5040 , the physical, spatial reorientation is complete and the next-subject set of multi-modal molecular images can be acquired at step  670  of  FIG. 13 . 
     In another embodiment the following method is used for step  660  of  FIG. 13 . Referring to the workflow shown in  FIG. 15 , image  520   a  is compared to image  525   b, c  and  d ; a calculation of the image difference between the two X-ray anatomical images is made at step  800 ; and a comparison of the image difference to a null (zero) image is made at step  810 . Where the comparison of the image difference to a null (zero) image is not satisfactory as shown in the “NO” branch of step  820 , the subject is physically, spatially reoriented according to its virtual, spatial correspondence to the reference image at step  830 , and the flow goes back to step  800  of  FIG. 15 . If the comparison of the image difference to a null (zero) image is satisfactory as shown in “YES” branch of step  820 , the physical, spatial reorientation is complete and the next-subject set of multi-modal molecular images can be acquired at step  670  of  FIG. 13 . 
     In yet another embodiment of the present invention the physical, spatial reorientations of the physical subjects involve comparing different animals as shown in  FIG. 16 . A plurality of small animals such as subject mice  900   a, b, c , and  d  are used in a multi-modal molecular imaging study and are loaded into animal chambers  910   a, b, c , and  d , respectively, whereby the loading and imaging may be in parallel. 
     As shown in the images of  FIG. 17  and the workflow chart in  FIG. 18 , a multi-subject test physical, spatial orientation is performed at step  1000 , followed by acquisition of a test multi-subject X-ray anatomical image  920  of the multi-subject mice “a”, “b”, “c” and “d” in system  100  at step  1010 . Image  920  is divided into image sections  925   a, b, c , and  d  of subject mice “a”, “b”, “c”, and “d”, respectively. The image sections  925   b, c , and  d  of subject mice “a”, “b”, “c”, and “d”, respectively, are compared to the image section  925   a  of subject mouse “a” using the matching criteria designed to match the physical, spatial orientation of the subject mice “b”, “c”, and “d” to the physical, spatial orientation of subject mouse “a” at step  1020 . The comparison may be made by a calculation of the difference between the image section  925   b, c , and  d  of each subject mouse “b”, “c”, and “d”, respectively, and the image section  925   a  of subject mouse “a”. Or the comparison may be according to the digital image processing method for image registration described in the U.S. patent of Chen et al. The comparison may be manual or automated. The comparison may be performed based on endogenous X-ray anatomical image contrast, such as from skeletal and/or soft tissue, or exogenous X-ray anatomical image contrast, such as injected, implanted, and/or otherwise attached radio-opaque imaging agents or devices. If the analysis of the output of the comparison at step  1020  is satisfactory, corresponding to the “YES” branch of step  1020 , a set of multi-subject multi-modal molecular images  940  may be acquired, step  1040 . As seen in  FIG. 17 , set  940  includes two multi-modal molecular images, an upper image  941   a  captured using a first molecular imaging mode and a lower image  941   b  captured using a second molecular imaging mode. The set of modes may include at least one of bright-field mode, dark-field mode, and radio isotopic mode. The set of multi-subject multi-modal molecular images  940  may include at least one image acquired using at least one mode included in the set of modes, wherein the set of multi-subject multi-modal molecular images  940  is co-registered with the test multi-subject X-ray anatomical image  920 . If the output of the comparison is unsatisfactory, corresponding to the “NO” branch of step  1020 , the immobilized subject mice  900   b, c , and  d  are physically, spatially reoriented at step  1030  to improve the comparison, whereby the physical, spatial reorientation may be determined by spatially mapping the results determined from the digital image processing method for image registration described by Chen et al. to the physical subjects  900   b, c , and  d , or the reorientation may be made by trial-and-error. The reorientation may be performed by manual means, or by robotic means controlled by the communication and computer control system  20  in the manner previously discussed but via rotational mechanisms  926   b, c , and  d  and X-Y translation mechanisms  928   b, c , and  d  as shown in  FIG. 16 . Steps  1010 ,  1015 ,  1020 , and  1030  are repeated, until the output of the comparison is satisfactory, thereby corresponding to the “YES” branch of step  1020  and a set of multi-subject multi-modal molecular images  940  is acquired, which is co-registered with a set of multi-subject X-ray anatomical images  930 . 
     In another embodiment the following statistical method is used for step  1030  of  FIG. 18 . Referring to the workflow shown in  FIG. 19 , the comparison of subject mouse “a” in X-ray anatomical image section  925   a  to the mice “b”, “c”, and “d” in X-ray anatomical image sections  925   b, c , and  d  is comprised of the steps of applying vector quantization to the X-ray anatomical image sections  925   a, b, c , and  d ; converting the X-ray anatomical image sections to vectorized X-ray anatomical image sections having corresponding local intensity information as derived respectively from the X-ray anatomical image sections  925   a, b, c , and  d  at step  2000 ; obtaining a joint statistical representation of the X-ray anatomical image sections by employing the vectorized image sections at step  2010 ; computing cost functions using the joint statistical representation of the X-ray anatomical image sections of subject mice “a”, “b”, “c”, and “d” at step  2020 ; selecting a reference X-ray anatomical image section (the image section of mouse “a”) from the X-ray anatomical image sections at step  2030 ; and evaluating the cost functions for each of subject mice “b”, “c”, and “d” at step  2040 . If the predetermined cost function criterion is unsatisfied as shown in the “NO” branch of step  2040 , subject mice “b”, “c”, and/or “d” are physically, spatially reoriented according to their virtual, spatial correspondence to the reference X-ray anatomical image section for subject mouse “a” at step  2050 , and the flow goes back to step  2000  of  FIG. 19 . If the predetermined cost function criterion is satisfied as shown in the “YES” branch of step  2040 , the physical, spatial reorientation is complete and a set of multi-subject multi-modal molecular images  940  can be acquired at step  1040  of  FIG. 18 . Persons skilled in the art understand that step  1030  can be implemented with or without vector quantization in step  2000 . 
     In another embodiment the following method is used for step  1030  of  FIG. 18 . Referring to the workflow shown in  FIG. 32 , the comparison of subject mouse “a” in X-ray anatomical image section  925   a  to the mice “b”, “c”, and “d” in X-ray anatomical image sections  925   b, c , and  d  is comprised of the steps of selecting a reference image section (X-ray anatomical image section of mouse a) at step  6000 ; applying an image registration algorithm (e.g. as described by Chen et al.) to X-ray anatomical image sections of mice  a, b, c , and  d  at step  6010 ; obtaining minimal cost function values from the image registration process at step  6020 ; obtaining virtual spatial displacement maps corresponding to the minimal cost functions from the image registration process at step  6030 ; and evaluating the cost functions at step  6040 . If the predetermined cost function criterion is unsatisfied as shown in the “NO” branch of step  6040 , the subject mice “b”, “c” and/or “d” are physically, spatially reoriented automatically or manually according to the virtual spatial displacement maps at step  6050 , and flow goes back to step  6000  of  FIG. 32 . If the predetermined cost function criterion is satisfied as shown in the “YES” branch of step  6040 , the physical, spatial reorientation is complete and a set of multi-subject multi-modal molecular images  940  can be acquired at step  1040  of  FIG. 18 . The spatial displacement map can be computed based on the virtual spatial transformation described by Chen et al. 
     In another embodiment the following method is used for step  1030  of  FIG. 18 . Referring to the workflow shown in  FIG. 20 , the X-ray anatomical image section  925   a  of subject mouse “a” is compared to the X-ray anatomical image sections  925   b, c , and  d  of subject mice “b”, “c”, and “d”, respectively, and a calculation of the X-ray anatomical image section differences between the images is made at step  3000 ; and a comparison of the image differences to a null (zero) image section is made at step  3010 . Where the comparison of the X-ray anatomical image section differences to a null (zero) image is not satisfactory as shown in the “NO” branch of step  3020 , the subject is physically, spatially reoriented according to its virtual spatial correspondence to the reference image at step  3030 , and the flow goes back to step  3000  of  FIG. 20 . If the comparison of the X-ray anatomical image section differences to a null (zero) image is satisfactory as shown in “YES” branch of step  3020 , the physical, spatial reorientation is complete and a set of multi-subject multi-modal molecular images can be acquired at step  1040 . 
     In another embodiment the problem of registering multi-modal molecular images is solved by virtually, spatially reorienting both the X-ray anatomical images and the multi-modal molecular images of the subject(s) using the same virtual spatial transformation parameters to achieve the desired registration in the resulting images. More specifically referring to  FIGS. 5A and 5B  and the workflow shown in  FIG. 22 , a first-time physical, spatial orientation is performed at step  3030 , followed by acquisition of a first-time X-ray anatomical image  120  at step  3040  and a first-time set of multi-modal molecular images  122  at step  3050  of subject  112  using system  100 . Regions-of-interest templates  3100  and  3110  are created using techniques familiar to those skilled in the art and include region of interest  3105  and regions of interest  3115   a  and  3115   b  in the first-time set of multi-modal molecular images  122  at step  3060 . Molecular signals are measured in the regions of interest  3105 ,  3115   a  and  b  at step  3070 .  FIG. 21  shows a graphical representation of the first-time molecular signals measured in regions of interest  3105 ,  3115   a  and  3115   b.    
     As shown in  FIGS. 7A and 7C  and the workflow shown in  FIG. 25 , a next-time physical, spatial orientation is performed step  3300 . A next-time X-ray anatomical image  3200  and a next-time set of multi-modal molecular images  3220  are acquired of subject  112  using the imaging system  100  at step  3310 . The next-time X-ray anatomical image  3200  is registered to the first-time X-ray anatomical image  120  at step  3320 . The image registration at step  3320  may be performed by using the calculation of the difference between the next-time test X-ray anatomical image  3200  and the first-time X-ray anatomical image  120 , or the image registration at step  3320  may be according to the digital image processing method for image registration described by Chen et al. The image registration may be manual or automated. The image registration may be performed based on endogenous X-ray anatomical image contrast, such as from skeletal and/or soft tissue, or exogenous X-ray anatomical image contrast, such as injected, implanted, and/or otherwise attached radio-opaque imaging agents or devices. Once the next-time X-ray anatomical image  3200  is registered to the first-time X-ray anatomical image  120 , the same spatial transformation parameters that were required to perform the image registration at step  3320  are applied to the next-time set of multi-modal molecular images as subsequently described with regard to  FIG. 26 , thereby creating a virtually, spatially reoriented next-time set of multi-modal molecular images at step  3330 . Next the regions-of-interest templates  3100  and  3110  are applied to the virtually, spatially reoriented next-time set of multi-modal molecular images  3220  at step  3340 , and the next-time signals measured in regions of interest  3105 ,  3115   a  and  b  are measured step  3350 . At step  3360  the signals are then compared to the signals measured at step  3070 .  FIGS. 23 and 24  shows graphical representations of the next-time molecular signals measured in regions of interest  3105 ,  3115   a  and  3115   b , excluding and including steps  3320  and  3330 , respectively, to demonstrate the advantage of the present invention. 
     In the embodiment described above the following statistical method is used for the image registration step  3320  of  FIG. 25 . Referring to the workflow shown in  FIG. 26 , the registration of the first-time X-ray anatomical image  3210  to the next-time X-ray anatomical image  3200 , is accomplished by steps of applying vector quantization to the first-time X-ray anatomical image  3210  and the next-time X-ray anatomical image  3200 ; converting these X-ray anatomical images to vectorized X-ray anatomical images having corresponding local intensity information as derived respectively from the X-ray anatomical images at step  3400 ; obtaining a joint statistical representation of the X-ray anatomical images by employing the vectorized X-ray anatomical images at step  3410 ; computing a cost function using the joint statistical representation of the X-ray anatomical images at step  3420 ; selecting a reference image (the first-time X-ray anatomical image) from the plurality of X-ray anatomical images at step  3430 ; and evaluating the cost function at step  3440 . If the predetermined cost function criterion is unsatisfied as shown in the “NO” branch of step  3440 , the next-time X-ray anatomical image  3200  is virtually, spatially reoriented at step  3450  and the flow goes back to step  3400 . If the predetermined cost function criterion is satisfied as shown in the “YES” branch of step  3440 , the virtual, spatial reorientation is complete, a virtually, spatially reoriented next-time X-ray anatomical image  3210  is produced, and the flow goes back to step  3330  of  FIG. 25 . 
     In another embodiment the following method is used for the image registration step  3320  of  FIG. 25 . Referring to the workflow shown in  FIG. 27 , using the first-time X-ray anatomical image  120  and the next-time X-ray anatomical image  3200  a calculation of the image difference between the two images is made at step  3500 ; and a comparison of the image difference to a null (zero) image is made at step  3510 . Where the comparison of the image difference to a null (zero) image is not satisfactory as shown in the “NO” branch of step  3520  the next-time X-ray anatomical image  3200  is virtually, spatially reoriented at step  3530  and the flow returns to step  3500 . If the comparison of the image difference to a null (zero) image is satisfactory as shown in “YES” branch of step  3520 , the virtual, spatial reorientation is complete, a virtually, spatially reoriented next-time X-ray anatomical image  3210  is produced, and the flow goes to step  3330  of  FIG. 25 . 
     It should be understood that the method described as registration of multi-modal molecular images and shown in  FIGS. 5A ,  5 B,  7 A,  7 C and  21  to  27  may be applied to any of the following scenarios; imaging a single subject at different times, imaging multiple subjects serially, and imaging multiple subjects in parallel. 
     The method of virtual, spatial reorientation of multi-modal molecular images is better suited for reproducing the spatial orientation when the molecular signals are closer to the surface of the subject and not significantly affected by the optical effects of tissue such as absorption and scattering, while the method of physical, spatial reorientation of the subject(s) is better suited for reproducing the spatial orientation when the molecular signals are deeper within the subject and are significantly affected by the optical effects of tissue such as absorption and scattering. However, it will be understood that the method of virtual, spatial orientation of multi-modal molecular images may be useful for reproducing the spatial orientation when the molecular signals are deeper within the subject, and that the method of physical, spatial reorientation of the subject(s) may be useful for reproducing the spatial orientation when the molecular signals are closer to the surface of the subject. 
     An example of use of an exogenous X-ray anatomical image contrast agent to facilitate the reproduction of spatial orientation is shown in  FIG. 28 . A radio opaque imaging agent  3600  is injected into the subject. The imaging agent provides contrast associated with the soft tissue, such as the organs and/or vasculature, of the subject. Such radio opaque imaging agents include barium, palladium, gold, and iodine. An example of use of an exogenous X-ray anatomical image contrast device to facilitate the reproduction of spatial orientation is shown in  FIG. 29 . Solid metal objects or pieces of metal foil  3610   a  and  b  are inserted and/or attached to the subject. 
     Another method for reproducing the spatial orientation of immobilized subjects in a multi-modal imaging system is shown in  FIGS. 34 to 41 . First, as shown in  FIGS. 34 ,  41 A and  41 B, a series of reference physical, spatial orientations of the immobilized subject(s) in the multi-modal imaging system is performed, whereby a reference X-ray anatomical image of the immobilized subject(s) is acquired for each physical, spatial orientation, step  7000 .  FIG. 34  shows a series of reference X-ray anatomical images of an immobilized mouse in which the spatial orientation, in this case the cranio-caudal rotation angle, has been incremented by approximately 30 degrees from image to image over 360 degrees. Next, a gradient image and an opposite-gradient image for each reference X-ray anatomical image are calculated, step  7010  of  FIG. 41A . Methods for calculating a gradient image are known in the art; such methods involve application of an edge-detection kernel, for example a Prewitt kernel, Sobel kernel, or variations thereof, to the image. For example, the series of gradient images shown in  FIG. 35A  was obtained by taking the X-ray anatomical images shown in  FIG. 34  and applying the following 7×7 left-to-right edge-detection kernel: 
                                                                    +1   +1   +1   +1   −1   −1   −1           +1   +1   +1   +1   −1   −1   −1           +1   +1   +1   +1   −1   −1   −1           +1   +1   +1   −6   −1   −1   −1           +1   +1   +1   +1   −1   −1   −1           +1   +1   +1   +1   −1   −1   −1           +1   +1   +1   +1   −1   −1   −1                        
This kernel is appropriate because the direction of the cranio-caudal axis is from the top to bottom in the images, so the edges of interest (e.g., the edges of the pubis bones) will be detected by a left-to-right edge-detection kernel. The series of opposite-gradient images shown in  FIG. 35B  was obtained by taking the X-ray anatomical images shown in  FIG. 34  and applying the following 7×7 right-to-left edge-detection kernel:
 
     
       
         
           
               
               
               
               
               
               
               
               
             
               
                   
                   
               
             
            
               
                   
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     Next, a line profile for each gradient image and opposite-gradient image is captured, step  7020  of  FIG. 41A . For example, the location of such a line profile is shown in  FIGS. 35A  and B, where the line profile intersects the pubis bones of the mouse. A plurality of line profiles may also be appropriate. Next, the abscissae of the line profiles from the opposite-gradient images are reversed, step  7030 . For example, the series of line profiles shown in  FIG. 36  include the gradient image line profiles (solid curves) plotted with the abscissae based on the gradient image left-to-right coordinates, and the opposite-gradient image line profiles (dashed curves) plotted with the abscissae reversed from the opposite-gradient image left-to-right coordinates. Next, for each reference physical, spatial orientation, the cross-correlation of the line profile from the gradient image and the abscissa-reversed line profile from the opposite-gradient image is calculated, step  7040 . Alternatively, those skilled in the art would recognize that it is mathematically equivalent to forego the calculation of the opposite-gradient images and simply to take the line profiles from the gradient images, reverse their abscissae, negate their ordinates, and calculate the cross-correlations of the results with the original line profiles. Next, for each reference physical, spatial orientation, the maximum of the resulting cross-correlations are determined and plotted vs. physical, spatial orientation (e.g., cranio-caudal rotation angle), for example as shown in  FIG. 37 , step  7050 . Next, the peak positions in the plot of cross-correlation maximum vs. reference physical, spatial orientation are assigned to prone and supine physical, spatial orientations, step  7060 . For the plot shown in  FIG. 37 , the prone physical, spatial orientations are assigned to 0 degrees and 360 degrees, and the supine physical, spatial orientation is assigned to 180 degrees. This assignment is enabled by the fact that the peaks in the plot of cross-correlation maximum vs. physical, spatial orientation are indicative of the physical, spatial orientations that exhibit maximal bilateral symmetry. The assignment to prone and supine physical, spatial orientations presumes prior knowledge of the approximate physical, spatial relationship of the subject to the imaging system in the series of X-ray anatomical images to be able to distinguish the prone physical, spatial orientations from the supine physical, spatial orientations. Next, the reference physical, spatial orientations corresponding to prone and supine physical, spatial orientations are used as references for achieving an arbitrary physical, spatial orientation, step  7070 . 
     For example,  FIG. 33A  shows that the optimal physical, spatial orientation for detecting a fluorescence molecular signal from the right kidney is at −150 degrees (or, equivalently, 210 degrees), where 0 degrees is defined as the prone position and clockwise rotation is defined as being a negative rotation, so upon determination of the physical, spatial orientation (e.g., cranio-caudal rotation angle) corresponding to the prone physical, spatial orientation, the subject would be rotated −150 degrees to obtain the optimal physical, spatial orientation for detecting a fluorescence molecular signal from the right kidney. 
     Next, reference sets of multi-modal molecular images of the immobilized subjects using a set of modes of the multi-modal imaging system are acquired, whereby the sets of multi-modal molecular images include at least one image acquired using at least one mode included in the set of modes, step  7080  of  FIG. 41A . Next, for example at a later time for the same subject, or upon substitution of a different subject, a series of test physical, spatial orientations of the immobilized subject(s) in the multi-modal imaging system is performed, whereby a test X-ray anatomical image of the immobilized subject(s) is acquired for each physical, spatial orientation, step  7090  of  FIG. 41B . For example, a series of test X-ray anatomical images of an immobilized mouse whereby the physical, spatial orientation, in this case the cranio-caudal rotation angle, has been incremented by 30 degrees would be as shown in  FIG. 34 , but shifted one image to the right due to a happenstance 30 degree difference in the initial animal positioning, as illustrated. 
     Next, a gradient image and an opposite-gradient image for each test X-ray anatomical image is calculated, step  7100 . For example, the series of gradient images shown in  FIG. 38A  were obtained by taking the X-ray anatomical images shown in  FIG. 34 , shifted one image to the right due to a happenstance 30 degree difference in the initial animal positioning, and applying the 7×7 left-to-right edge-detection kernel as described previously; and the series of opposite-gradient images shown in  FIG. 38B  were obtained by taking the X-ray anatomical images shown in  FIG. 34 , shifted one image to the right due to a happenstance 30 degree difference in the initial animal positioning, and applying the 7×7 right-to-left edge-detection kernel as described previously. 
     Next, a line profile for each gradient image and opposite-gradient image is captured, step  7110 . For example, the location of such a line profile is shown in  FIGS. 38A  and B, whereby the line profile intersects the pubis bones of the mouse. A plurality of line profiles may also be appropriate. Next, the abscissae of the line profiles from the opposite-gradient images are reversed, step  7120 . For example, the series of line profiles shown in  FIG. 39  include the gradient image line profiles (solid curves) plotted with the abscissae based on the gradient image left-to-right coordinates, and the opposite-gradient image line profiles (dashed curves) plotted with the abscissae reversed from the opposite-gradient image left-to-right coordinates. 
     Next, for each test physical, spatial orientation, the cross-correlation of the line profile from the gradient image and the abscissa-reversed line profile from the opposite-gradient image is calculated, step  7130 . Alternatively, those skilled in the art would recognize that it is mathematically equivalent to forego the calculation of the opposite-gradient images and simply to take the line profiles from the gradient images, reverse their abscissae, negate their ordinates, and calculate the cross-correlations of the results with the original line profiles. 
     Next, for each test physical, spatial orientation, the maximum of the resulting cross-correlations are determined and plotted vs. physical, spatial orientation (e.g., cranio-caudal rotation angle), for example as shown in  FIG. 40 , step  7140 . Next, the peak positions in the plot of cross-correlation maximum vs. test spatial orientation are assigned to prone and supine physical, spatial orientations, step  7150 . For the plot shown in  FIG. 40 , the prone physical, spatial orientation is assigned to 150 degrees, and the supine physical, spatial orientation is assigned to 330 degrees. This assignment is enabled by the fact that the peaks in the plot of cross-correlation maximum vs. physical, spatial orientation are indicative of the physical, spatial orientations that exhibit maximal bilateral symmetry. The assignment to prone and supine physical, spatial orientations presumes prior knowledge of the approximate physical, spatial relationship of the subject to the imaging system in the series of X-ray anatomical images to be able to distinguish the prone physical, spatial orientations from the supine physical, spatial orientations. 
     Next, the test physical, spatial orientations corresponding to prone and supine physical, spatial orientations are used as references for achieving an arbitrary physical, spatial orientation, i.e., reproducing the arbitrary physical, spatial orientation achieved previously, for example −150 degree rotation from the prone physical, spatial orientation, step  7160 . 
     Finally, sets of multi-modal molecular images of the immobilized subjects using a set of modes of the multi-modal imaging system are acquired, whereby the sets of multi-modal molecular images include at least one image acquired using at least one mode included in the set of modes, step  7170 . Hence, the sets of multi-modal molecular images may be fairly compared to the reference sets of multi-modal molecular images by virtue of the reproduction of the physical, spatial orientation. 
     Although one or more line profiles may be used to assess the degree of bilateral symmetry of the X-ray anatomical images as described above, one may alternatively use a method involving analysis of gradient orientation histograms to assess the degree of bilateral symmetry of the X-ray anatomical images, for example as described in “Symmetry detection using gradient information” by C. Sun, Pattern Recognition Letters 16 (1995) 987-996, and “Fast Reflectional Symmetry Detection Using Orientation Histograms” by C. Sun and D. Si, Real-Time Imaging 5, 63-74, 1999. An embodiment using this method is described in  FIGS. 42A  and B. In this method, first a series of reference physical, spatial orientations of the immobilized subject(s) in the multi-modal imaging system is performed, whereby a reference X-ray anatomical image of the immobilized subject(s) is acquired for each physical, spatial orientation, step  8000 . Next, a gradient image and an orthogonal-gradient image for each reference X-ray anatomical image are calculated, step  8010 . Methods for calculating a gradient image are known in the art; such methods involve application of an edge-detection kernel, for example a Prewitt kernel, Sobel kernel, or variations thereof, to the image. 
     For example, the following 7×7 edge-detection kernel may be applied to calculate the gradient image: 
                                                                    +1   +1   +1   +1   −1   −1   −1           +1   +1   +1   +1   −1   −1   −1           +1   +1   +1   +1   −1   −1   −1           +1   +1   +1   −6   −1   −1   −1           +1   +1   +1   +1   −1   −1   −1           +1   +1   +1   +1   −1   −1   −1           +1   +1   +1   +1   −1   −1   −1                        
The following 7×7 edge-detection kernel may be applied to calculate the orthogonal-gradient image:
 
     
       
         
           
               
               
               
               
               
               
               
               
             
               
                   
                   
               
             
            
               
                   
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     Next, a gradient orientation image is calculated for each pair of gradient image and orthogonal-gradient image by calculating the inverse tangent of the pair, step  8020 . 
     Next, the gradient orientation histogram is calculated for each gradient orientation image, step  8030 . 
     Next, each gradient orientation histogram is analyzed to calculate the degree of the bilateral symmetry of the corresponding reference X-ray anatomical image which is plotted vs. reference spatial orientation (e.g., cranio-caudal rotation angle), step  8040 . 
     Next, peak positions are assigned in the plot of degree of bilateral symmetry vs. reference physical, spatial orientation to prone and supine physical, spatial orientations, step  8050 . 
     Next, reference physical, spatial orientations corresponding to prone and supine physical, spatial orientations are used as references for achieving an arbitrary physical, spatial orientation, step  8060 . For example,  FIG. 33A  shows that the optimal physical, spatial orientation for detecting a fluorescence molecular signal from the right kidney is at −150 degrees (or, equivalently, 210 degrees), where 0 degrees is defined as the prone position and clockwise rotation is defined as being a negative rotation, so upon determination of the physical, spatial orientation (e.g., cranio-caudal rotation angle) corresponding to the prone physical, spatial orientation, the subject would be rotated −150 degrees to obtain the optimal physical, spatial orientation for detecting a fluorescence molecular signal from the right kidney. 
     Next, reference sets of multi-modal molecular images of the immobilized subjects are acquired using a set of modes of the multi-modal imaging system, whereby the sets of multi-modal molecular images include at least one image acquired using at least one mode included in the set of modes, step  8070 . 
     Next, a series of test physical, spatial orientations of the immobilized subjects in the multi-modal imaging system is performed, whereby a test X-ray anatomical image of the immobilized subject(s) is acquired for each physical, spatial orientation, step  8080  in  FIG. 42B . 
     Next, a gradient image and an orthogonal-gradient image for each test X-ray anatomical image is calculated, step  8090 . 
     Next, a gradient orientation image is calculated for each pair of gradient image and orthogonal-gradient image by calculating the inverse tangent of the pair, step  8100 . Next, the gradient orientation histogram is calculated for each gradient orientation image, step  8110 . 
     Next, each gradient orientation histogram is analyzed to calculate the degree of the bilateral symmetry of the corresponding test X-ray anatomical image which is plotted vs. test physical, spatial orientation (e.g., cranio-caudal rotation angle), step  8120 . 
     Next, peak positions are assigned in the plot of degree of bilateral symmetry vs. test physical, spatial orientation to prone and supine physical, spatial orientations, step  8130 . 
     Next, test physical, spatial orientations corresponding to prone and supine physical, spatial orientations are used as references for achieving an arbitrary physical, spatial orientation, step  8140 . 
     Finally, sets of multi-modal molecular images of the immobilized subjects are acquired using a set of modes of the multi-modal imaging system, whereby the sets of multi-modal molecular images include at least one image acquired using at least one mode included in the set of modes, step  8150 . Hence, the sets of multi-modal molecular images may be fairly compared to the reference sets of multi-modal molecular images by virtue of the reproduction of the physical, spatial orientation. 
     Other methods for assessing the degree of bilateral symmetry of X-ray anatomical images are described in the art and are applicable to this invention; for example, “Optimal Detection of Symmetry Axis in Digital Chest X-ray Images” by C. Vinhais and A. Campilho, F. J. Perales et al. (Eds.): IbPRIA 2003, LNCS 2652, pp. 1082-1089, 2003, and references cited therein. 
     Another method for reproducing the physical, spatial orientation of immobilized subjects in a multi-modal imaging system is shown in  FIGS. 43 to 50 . First, as shown in  FIGS. 43 ,  50 A and  50 B, a series of reference physical, spatial orientations of the immobilized subject(s) in the multi-modal imaging system is performed, whereby a reference X-ray anatomical image of the immobilized subject(s) is acquired for each physical, spatial orientation, step  9000 .  FIG. 43  shows a series of reference X-ray anatomical images of an immobilized mouse in which the physical, spatial orientation, in this case the cranio-caudal rotation angle, has been incremented by approximately 5 degrees from image to image. 
     Next, an X-ray density image is calculated for each reference X-ray anatomical image, step  9010 .  FIG. 44  shows X-ray density images corresponding to the images in  FIG. 43 . The calculation of the X-ray density images, i.e., conversion of the image intensity scale to an X-ray density scale, is achieved using methods well-known to those of ordinary skill in the art. 
     Next, pixels with X-ray density less than a predetermined threshold are set to zero (i.e., discarded), and pixels with X-ray density greater than or equal to the predetermined threshold are set to one (i.e., retained), in other words a binary thresholding operation, step  9020 . The predetermined threshold is designed to substantially discard pixels corresponding to soft-tissue (e.g., muscle tissue, intestines, etc.) and to substantially retain pixels corresponding to skeletal tissue. For example, a threshold value of approximately 0.9 has been empirically found to suffice for mice weighing 20-25 grams, and was used to obtain the series of binary thresholded images shown in  FIG. 45  based on the series of X-ray density images of  FIG. 44 . Hence, the reason for conversion of the original images to X-ray density scale at step  9010  is to provide calibrated images for binary thresholding and thereby remove all image intensity scale dependence on factors such as X-ray source intensity, phosphor screen speed, exposure time, and sensor speed. 
     Next, a gradient image for each reference X-ray anatomical image is calculated, step  9030 . Methods for calculating a gradient image are known in the art; such methods involve application of an edge-detection kernel, for example a Prewitt kernel, Sobel kernel, or variations thereof, to the image. For example, the series of gradient images shown in  FIG. 46  was obtained by taking the X-ray anatomical images shown in  FIG. 43  and applying the following 7×7 left-to-right edge-detection kernel: 
     
       
         
           
               
               
               
               
               
               
               
               
             
               
                   
                   
               
             
            
               
                   
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     This kernel is appropriate because the direction of the cranio-caudal axis is from the top to bottom in the images, so the edges of interest will be detected by a left-to-right edge-detection kernel. Alternatively, a right-to-left edge detection kernel would serve equivalently. 
     Next, the results of step  9020  of  FIG. 50A  are imagewise (that is, pixel by pixel) multiplied by the results of step  9030  in step  9040 . For example,  FIG. 47  shows the series of images of  FIG. 45  imagewise multiplied by the series of images of  FIG. 46 . The purpose of step  9040  is to use the results of the binary thresholding operation of step  9020  to mask the gradient images of step  9030 , hence isolating and retaining the gradient values due to the skeletal features and discarding the gradient values due to soft-tissue, especially the boundary of the animal. 
     Next, the imagewise absolute values of the results of step  9040  are calculated, step  9050 . For example,  FIG. 48  shows the imagewise absolute value of the series of images of  FIG. 47 . The calculation of the imagewise absolute values is necessary to assess the magnitude of the gradient values. Alternatively, any even function may be performed on the output of step  9040 . Alternatively, the calculation of the imagewise absolute values or any even function could be performed on the results of step  9030  instead of the results of step  9040 , and then those results could be used as the input to step  9040  instead of the results of step  9030 . 
     Next, the sum within a predetermined region of interest is calculated for the results of step  9050  in step  9060 . The predetermined region of interest is chosen so as to include sufficient skeletal features to assess the overall skeletal alignment of the animal with respect to the cranio-caudal rotation axis: when the cranio-caudal rotation angle of the animal is other than those corresponding to prone or supine physical, spatial orientations, then many dominant skeletal features such as the spine and femurs are askew with respect to the cranio-caudal rotation axis due to the projection of the X-ray shadow of the natural geometry of these features onto the phosphor screen; however, when the cranio-caudal rotation angle of the animal corresponds to prone or supine physical, spatial orientations, then many dominant skeletal features such as the spine and femurs appear aligned to the cranio-caudal rotation axis. The predetermined region of interest may include the entire animal as shown in  FIG. 43 to 48 , or may alternatively include only a portion of the animal (such as below the head, or around and below the pelvis). 
     Next, the peak positions in the plot of the results of step  9060  vs. reference physical, spatial orientation are assigned to prone and supine physical, spatial orientations, step  9070  of  FIG. 50A . For example, such a plot is shown in  FIG. 49 , showing the peak corresponding to the prone physical, spatial orientation. The plot shows a relative peak height above background of 15%, which is sufficient to identify the peak position. 
     Next, the reference physical, spatial orientations corresponding to prone and supine physical, spatial orientations are used as references for achieving an arbitrary physical, spatial orientation, step  9080 . 
     Next, reference sets of multi-modal molecular images of the immobilized subjects using a set of modes of the multi-modal imaging system are acquired, whereby the sets of multi-modal molecular images include at least one image acquired using at least one mode included in the set of modes, step  9090 . 
     Next, a series of test physical, spatial orientations of the immobilized subject(s) in the multi-modal imaging system is performed, whereby a test X-ray anatomical image of the immobilized subject(s) is acquired for each physical, spatial orientation, step  9100  in  FIG. 50B . 
     Next, an X-ray density image is calculated for each test X-ray anatomical image, step  9110 . 
     Next, pixels with X-ray density less than the predetermined threshold used in step  9020  are set to zero (i.e., discarded), and pixels with X-ray density greater than or equal to the predetermined threshold used in step  9020  are set to one (i.e., retained), in other words a binary thresholding operation, step;  9120 . 
     Next, a gradient image for each test X-ray anatomical image is calculated, step  9130 . 
     Next, the results of step  9120  are imagewise multiplied by the results of step  9130 , step  9140 . 
     Next, the imagewise absolute values of the results of step  9140  are calculated, step  9150 . 
     Next, the sum within a predetermined region of interest is calculated for the results of step  9150 , step  9160 . 
     Next, the peak positions in the plot of the results of step  9160  vs. test physical, spatial orientation are assigned to prone and supine orientations, step  9170 . 
     Next, the test physical, spatial orientations corresponding to prone and supine physical, spatial orientations are used as references for achieving an arbitrary physical, spatial orientation, step  9180 . 
     Finally, sets of multi-modal molecular images of the immobilized subjects using a set of modes of the multi-modal imaging system are acquired, whereby the sets of multi-modal molecular images include at least one image acquired using at least one mode included in the set of modes, step  9190 . 
     The invention has been described in detail with particular reference to a presently preferred embodiment, but it will be understood that variations and modifications can be effected within the spirit and scope of the invention. The presently disclosed embodiments are therefore considered in all respects to be illustrative and not restrictive. The scope of the invention will be indicated by the claims to be submitted in a later-filed regular application, and all changes that come within the meaning and range of equivalents thereof will be intended to be embraced therein. 
     PARTS LIST 
     
         
           10  electronic imaging system 
           12  light source 
           14  optical compartment 
           16  mirror 
           18  lens and camera system 
           20  communication and computer control system 
           22  display device, computer monitor 
           100  imaging system 
           102  X-ray source 
           104  sample object stage 
           106  fiber optics 
           108  sample environment 
           110  access means or member 
           112  subject mouse 
           114  respiratory device 
           116  tube 
           118  cylindrical sample chamber or tube 
           120  first-time X-ray anatomical image 
           122  first-time set of multi-modal molecular images 
           124  next-time test X-ray anatomical image 
           126  rotational mechanism 
           128  translation mechanism 
           130  next-time X-ray anatomical image after physical, spatial reorientation 
           132  next-time set of multi-modal molecular images 
           200 - 420  process steps 
           500   a, b, c, d  subject mouse 
           510   a, b, c, d  cylindrical sample tube 
           520   a  first-subject X-ray anatomical image 
           525   b, c, d  next-subject test X-ray anatomical image 
           530   a  first-subject set of multi-modal molecular images 
           531   a, b  images 
           535   b, c, d  next-subject X-ray anatomical image after physical, spatial reorientation 
           540   b, c, d  next-subject set of multi-modal molecular images 
           541   a  next-subject multi-modal molecular images captured using a first molecular imaging mode 
           541   b  next-subject multi-modal molecular images captured using a second molecular imaging mode 
           542   a  next-subject multi-modal molecular images captured using a first molecular imaging mode 
           542   b  next-subject multi-modal molecular images captured using a second molecular imaging mode 
           543   a  next-subject multi-modal molecular images captured using a first molecular imaging mode 
           543   b  next-subject multi-modal molecular images captured using a second molecular imaging mode 
           600 - 830  process steps 
           900   a, b, c, d  subject mice 
           910   a, b, c, d  animal chambers 
           920  test multi-subject X-ray anatomical image 
           925   a, b, c, d  image sections 
           926   a, b, c, d  rotational mechanism 
           928   a, b, c, d  translation mechanism 
           930  multi-subject X-ray anatomical image after physical, spatial reorientation 
           940  set of multi-subject multi-modal molecular images 
           941   a  multi-subject multi-modal molecular images captured using a first molecular imaging mode 
           941   b  multi-subject multi-modal molecular images captured using a second molecular imaging mode 
           1000 - 3070  process steps 
           3100  regions-of-interest template 
           3105  region of interest 
           3110  regions-of-interest template 
           3115   a, b  regions of interest 
           3200  next-time X-ray anatomical image 
           3210  virtually, spatially reoriented next-time X-ray anatomical image 
           3220  virtually, spatially reoriented next-time set of multi-modal molecular images 
           3300 - 3530  process steps 
           3600  exogenous X-ray anatomical image contrast agent 
           3610   a, b  exogenous X-ray anatomical image contrast devices 
           4000 - 9190  process steps