Abstract:
The method implements time-optimized acquisition of special spectra using a scanning microscope ( 100 ), for which purpose the spectrum ( 50 ) is subjected to bisecting interval measurements.

Description:
CROSS REFERENCE TO RELATED APPLICATIONS  
         [0001]    This application claims priority to German patent application DE 102 18 706.1, filed on Apr. 26, 2002, which is incorporated by reference herein.  
         BACKGROUND OF INVENTION  
         [0002]    The invention concerns a method for time-optimized acquisition of special spectra using a scanning microscope.  
           [0003]    In fluorescence microscopy, the specimens to be examined are generally stained with dyes that, as a result of excitation by means of an excitation light beam, emit detected light that has a spectral composition characteristic of the dye. Using a scanning microscope, it is possible to detect in a spectral region from 300 nm to approx. 1000 nm. The special emission spectra of the dyes lie somewhere in the spectral region from 300 nm to 1100 nm. The entire spectral region is thus scanned in order to locate the special spectra. This is time-consuming, and the radiation stress (e.g. bleaching, thermal damage, etc.) on the specimens being examined is high.  
           [0004]    Those specimens are often no longer usable for further examinations. Since a large expenditure of time and money is required to produce specimens for microscopic examination, the disadvantage of existing systems is that the specimens are exhausted by phototoxic effects simply by looking for the special spectra, without thereby obtaining experimental results or data.  
           [0005]    German Patent Application DE 100 06 800.6 discloses an apparatus for selecting and detecting at least one spectral region of a spectrally spread light beam (SP module). Selection means embodied as sliders are provided in the spread-out light beam in order thereby to deflect portions of the spread-out light beam onto various detectors. The signals of the detectors are then used for image generation. DE 100 06 800.6 does not disclose actuation of the sliders in such a way as to make possible rapid and reliable detection of a special spectrum.  
         SUMMARY OF THE INVENTION  
         [0006]    It is the object of the invention to create a method making possible rapid detection, with little specimen impact, of the location of an emission spectrum of a specimen.  
           [0007]    This object is achieved by way of a method comprising the steps:  
           [0008]    a) subdividing a complete spectrum, in which at least one special spectrum is located, into at least two intervals;  
           [0009]    b) determining the intensity of the light in the individual intervals;  
           [0010]    c) selecting one interval in which the intensity lies above a specific threshold (T);  
           [0011]    d) subdividing the selected interval into at least two further intervals;  
           [0012]    e) performing steps b) through c) until the size of the interval corresponds to the lower limit of measurement accuracy;  
           [0013]    f) determining the location of the special spectrum in the complete spectrum on the basis of the information about intensities in the selected intervals;  
           [0014]    g) linearly measuring the special spectrum; and  
           [0015]    h) deriving a model spectrum.  
           [0016]    The method for time-optimized acquisition of special spectra (emission spectra) using a scanning microscope is implemented in several steps. Firstly a complete spectrum to be examined, within which at least one special spectrum (emission spectrum) is located, is split into at least two intervals. The interval in which the intensity lies above a specific threshold is selected. That interval is split into at least two further intervals, and the procedure is continued until the size of the interval corresponds to the lower limit of the scanning microscope&#39;s measurement accuracy. The location of the special spectrum in the complete spectrum is defined, and an interval around it is created and is measured linearly.  
           [0017]    It is conceivable for the intervals each to have the same width and to correspond together to the width of the previous interval.  
           [0018]    Splitting of the overall spectrum is performed using sliders of a mirror stop arrangement of an SP module, the sliders being moved in motorized fashion and the method being controlled by a computer system.  
           [0019]    The invention has the advantage that after a single radiation impact on the specimen with simultaneous acquisition of the essential properties, it is possible to “play with” and learn about the specimen characteristics without causing further damage. Also possible for this purpose is a demo variant which reads the data set from a memory (hard drive, RAM, CD-ROM). This greatly minimizes training time on a confocal scanning microscope, reducing the impact on expensive specimens.  
           [0020]    With unknown specimens, for example specimens exhibiting considerable autofluorescence, or with mutants (manipulated by genetic engineering and given a fluorescent label), it is also possible to begin with a lambda scan in order to narrow down by experiment the best conditions for proceeding further. This offers substantial customer benefits. Once optimum settings have been made interactively on the basis of the acquired spectrum, the values can be loaded directly into the SP module so that the best possible images can be made with that data set.  
           [0021]    The operating principle of an SP module can be adapted, in terms of mathematical simulation, relatively accurately to the operating principle of the real SP module. The operating principles can be transferred by simulation into the software plane. There, however, they are automatically converted into a type of inverse filter or the like. The true value of the software module becomes apparent when an AOBS module, which obtains the essential spectral characteristics substantially better than conventional filter systems, is also integrated into the structure of the scanning microscope.  
           [0022]    Further advantageous embodiments of the invention are evident from the dependent claims.  
       
    
    
     BRIEF DESCRIPTION OF DRAWINGS  
       [0023]    The subject matter of the invention is depicted schematically in the drawings and will be described below with reference to the Figures, in which:  
         [0024]    [0024]FIG. 1 schematically depicts a scanning microscope.  
         [0025]    [0025]FIG. 2 schematically depicts a scanning microscope, an SP module being placed in front of the detector;  
         [0026]    [0026]FIG. 3 schematically depicts the SP module in detail;  
         [0027]    [0027]FIG. 4 a  schematically depicts a first step for acquisition of a spectrum;  
         [0028]    [0028]FIG. 4 b  schematically depicts a second step for acquisition of a spectrum;  
         [0029]    [0029]FIG. 4 c  schematically depicts a third step for acquisition of a spectrum; and  
         [0030]    [0030]FIG. 5 graphically depicts a complete spectrum, showing an allocation of the vectors necessary for the calculation. 
     
    
     DETAILED DESCRIPTION  
       [0031]    [0031]FIG. 1 schematically shows an exemplary embodiment of a confocal scanning microscope  100 . This is not, however, to be construed as a limitation of the invention: it is sufficiently clear to one skilled in the art that the invention can also be implemented with a conventional scanning microscope. Illuminating light beam  3  coming from at least one illumination system  1  is directed by a beam splitter or a suitable deflection means  5  to a scanning module  7 . Before illuminating light beam  3  encounters deflection means, it passes through an illumination pinhole  6 . Scanning module  7  encompasses a gimbal-mounted scanning mirror  9  that guides illuminating light beam  3  through a scanning optical system  12  and a microscope optical system  13 , over or through a specimen  15 . In the case of non-transparent specimens  15 , illuminating light beam  3  is guided over the specimen surface. With biological specimens  15  (preparations) or transparent specimens, illuminating light beam  3  can also be guided through specimen  15 . For that purpose, non-luminescent preparations are optionally prepared with a suitable dye (not depicted, since it is established existing art). The dyes present in the specimen are excited by illuminating light beam  3  and each emit light in a separate characteristic region of the spectrum. This light proceeding from specimen  15  defines a detected light beam  17 . This travels through microscope optical system  13  and scanning optical system  12  and via scanning module  7  to deflection means  5 , passes through the latter, and arrives via a detection pinhole  18  at at least one detector  19 , which is embodied as a photomultiplier. It is clear to one skilled in the art that other detection components, e.g. diodes, diode arrays, photomultiplier arrays, CCD chips, or CMOS image sensors, can also be used. Detected light beam  17  proceeding from and defined by specimen  15  is depicted in FIG. 1 as a dashed line. In detector  19 , electrical detected signals proportional to the power level of the light proceeding from specimen  15  are generated. Since, as already mentioned above, light of only one wavelength is emitted from specimen  15 , it is advisable to insert in front of the at least one detector  19  a selection means  21  for the spectrum proceeding from the specimen. The data generated by detector  19  are forwarded to a computer system  23 . At least one peripheral  27  is associated with computer system  23 . The peripheral can be, for example, a display on which the user receives instructions for adjusting the scanning microscope or can view the present setup and also the image data in graphical form. Also associated with computer system  23  is an input means that comprises, for example, a keyboard  28 , an adjusting apparatus  29  for the components of the microscope system, and a mouse  30 .  
         [0032]    [0032]FIG. 2 shows the embodiment of a scanning microscope in which an SP module  20  is arranged in front of the at least one detector  19  as selection means. All other elements shown in FIG. 2 are identical to those of FIG. 1, so that they need not be mentioned again in the description referring to FIG. 2. SP module  20  (FIG. 2) is embodied in such a way that it can acquire a complete lambda scan, i.e. one that records all the wavelengths proceeding from specimen  15 . The data are transferred to computer system  23  and can then be displayed, in a manner definable by the user, on display  27 . Detected light beam  17  is spatially spectrally divided with a prism  31 . Another possibility for spectral division is the use of a reflective or transmissive grating. The spectrally divided light fan  32  is focused with focusing optical system  33 , and then strikes a mirror stop arrangement  34 ,  35 . Mirror stop arrangement  34 ,  35 , the means for spectral spatial division, focusing optical system  33 , and detectors  36  and  37  are together referred to as SP module  20  (or the multi-band detector).  
         [0033]    As is evident from FIG. 3, by means of mirror stop arrangement  34 ,  35  a desired portion of the spectrum can be systematically selected. In the exemplary embodiment depicted here, mirror stop arrangement  34 ,  35  is equipped with a first and a second slider  40  and  41 . It is self-evident that for the selection of more than two spectral regions, a corresponding number of sliders must be provided. A first motor  44  is associated with first slider  40 , and a second motor  45  with second slider  41 . Motors  44  and  45  cause a displacement, described in accordance with the method below, of sliders  40  and  41 . As a result of the displacement of sliders  40  and  41 , only a portion of the divided light fan  32  of detected light beam  17 , which contains only light of the selected spectral region, passes through mirror stop arrangement  34 ,  35  and is detected by detector  36 , which is embodied as a photomultiplier. Another portion of the divided light fan  32  is reflected at mirror stop arrangement  35  and arrives at detector  37 , which is also embodied as a photomultiplier.  
         [0034]    The method is depicted schematically in FIGS. 4 a  through  4   c.  Instead of subdividing the spectrum into individual small intervals of equal size and scanning them in sequential and linear fashion, what is used here is e.g. a bisection approach. As depicted in FIG. 4 a,  spectrum  50  (from λ Min  through λ Max ) is subdivided into a first and a second interval  51  and  52 . It is especially advantageous if first and second interval  51  and  52  are identical in size. This is not, however, absolutely necessary. If the light measurement in second interval  52  is below a threshold T, then that interval  52  is not searched further. In first interval  51 , the measured value is greater than the defined threshold T, and searching therefore continues in first interval  51  (see FIG. 4 b ). As already described in FIG. 3, sliders  40  and  41  are displaced in such a way that a region of complete spectrum  50  corresponding to the first interval is measured with first detector  36 , and a region of the spectrum corresponding to second interval  52  is measured with second detector  37 . The image for first interval  51  is summed to yield an average or summed grayscale value, and compared to threshold T. The same procedure is used for second interval  52 . In first interval  51 , the measured grayscale value is greater than threshold T, so that here a splitting of first interval  51  is performed (see FIG. 4 b ).  
         [0035]    Bisection in first interval  51  then continues. First interval  51  is thus further subdivided by generating a third and fourth interval  53  and  54  in the first interval. This is done in the same way as already described in FIG. 4 a.  From third and fourth interval  53  and  54 , a selection is then made of the one that in turn lies above the defined threshold T. FIG. 4 c  then depicts the situation in which the same procedure has been applied to fourth interval  54  using the method described above. In the example depicted in FIG. 4 c,  the smallest step corresponding to the measurement accuracy has been arrived at. Here the fourth interval is subdivided further into a fifth and sixth interval  55  and  56 . The measurement accuracy, i.e. the extent to which subdivision of the intervals is to continue, is defined by the user or selected by the computer based on the criterion of whether more information is being gained; this is generally implemented, although with no limitation as to generality, by means of thresholds. As already described in FIG. 4 a,  mirror sliders  40 ,  41  are moved correspondingly when setting the desired intervals.  
         [0036]    [0036]FIG. 5 depicts, by way of example, a fluorescence spectrum  60  having sixteen support lines  60   1 ,  60   2 , . . .  60   16 . Fluorescence spectra have a relatively limited extent on the lambda axis, i.e. they do not extend over the entire region of a spectrum (from λ Min  to λ Max ). This invention results in a considerable time savings in determining the location of, and subsequently acquiring, a spectrum. For example, if there are 1,000 support points for the region from λ Min  to λ Max  and the spectrum to be measured is itself only 200 support points wide, only approx. log(1000)+200=210 measurements are needed here. With the conventional linear measurement method, approximately 1,000 measurements must be performed. In this concrete example, the invention accelerates measurement by a factor of approximately five. The speed-up value depends on the actual spectra being examined; experience indicates that they are spectrally small, and that the model presented above is realistic. In the example depicted in FIG. 5, the system requires four intervals or four measurements  64  in order to find the starting point. After that, a maximum of six scans  66  are required to acquire the spectrum, support points  60   4 ,  60   5  through  60   9  being individually measured in order to acquire the spectrum. The ten measurements are only slightly fewer than all  16  of the example depicted in FIG. 5 needed to acquire a spectrum, but the logarithm (the logarithm base being defined by the actual number of detectors present) decreases very rapidly as N rises, and the advantage gained with this method becomes that much more appreciable.  
         [0037]    A further alternative would be a full-width search over the complete spectrum between λ Min  and λ Max , also examining changes in the cumulative grayscale values along the way. If, for example, the sum of the lower subintervals is coincidentally equal to the sum of the parent intervals, this indicates that everything therein is very homogeneous, and scanning of the rest of the sub-tree of intervals can be discontinued. This yields a further time advantage.  
         [0038]    Because several intervals are scanned in the method according to the present invention, and thus a multi-scale match is performed, the spectrum can be described more accurately than if it were scanned through in linear fashion. Information at the finest scale, and the log(N) information from the higher scales, is obtained for each scanned spectral region. This can be utilized to fit the information to a higher-dimensional model (polynomial, splines, etc.) that explains discrepancies between the measurement data at different scales. This can be used to produce a smoothed spectrum (noise reduction) or to obtain super-resolution (spectrum as higher-order model, polynomial, spline). This can be explained as follows. With these assumptions:  
       I   i   N                         
 
         [0039]    is the light measurement from the i-th interval of a measurement using N intervals (i.e. we are in the log(N)-th step of bisection);  
       λ   i     N   +   1                           
 
         [0040]    are the associated interval limits;  
         [0041]    is the real spectrum; and  
         [0042]    is the spectral model, determined from these measurements, that approximates the real spectrum and contains the parameter vector ξ as the model&#39;s degree of freedom,  
         [0043]    the set of determination equations for the measurement is  
               I   i   N     =       ∫     λ   i   N       λ     i   +   1     N              I        (   λ   )               λ                 (   1   )                               
 
         [0044]    which must also be valid for the selected model l(λ,ξ)  
         [0045]    in the following form:  
               I   i   N     =       ∫     λ   i   N       λ     i   +   1     N              I        (     λ   ,   ξ     )               λ                 (   2   )                               
 
         [0046]    In the application from the existing art (without this method), only a one-to-one correlation is made. There are only N measurements  
       I   i   N                         
 
         [0047]    , and only exactly those measurements  
       I   i   N                         
 
         [0048]    can be selected as the spectral model l(λ,ξ)  
         [0049]    (without packing in more information). Applying this method to the same model with N degrees of freedom yields, in addition to those N measurements, an additional N/2 from the previous bisection step, N/4 from the one before that, etc.  
         [0050]    This yields  
               N   Total     =     N   +     N   2     +     N   4     +     N   8     +     N   16     +   …             (   3   )                               
 
         [0051]    measurements that must be mapped onto N degrees of freedom, resulting in a faster measurement operation as well as much more information about the spectrum. Redundant equations of this kind are solved, according to the existing art, using linear least-squares methods such as the Penrose-Moore pseudoinverse or other methods based on singular value decomposition (the list of numerical methods applicable here is very long, and not limiting for the purposes of this Application), which offer noise reduction as an inherent advantage.  
         [0052]    It should also be mentioned that this method is integrated into the image production system of a scanning microscope. In this context, “acquisition” in the description above is to be construed as the acquisition of individual pixels, individual lines, individual images, or individual volumes. The actual manner of implementation is left to the imagination of one skilled in the art, and is not affected by this document.  
         [0053]    A further possibility is to assign a different mathematical architecture for the spectral model l(λ,ξ)  
         [0054]    .A wide variety of different methods are possible here. Examples include Bezier curves such as those used in CAD for surface modeling, general splines that are widely utilized in signal processing and have been investigated for image processing, kernel regression methods from statistics, radially based networks, or methods that are commonly used in spectroscopy. These have the advantage of deriving an analog component from discrete measurements, and offer a great deal more than currently existing methods.