Patent Publication Number: US-2015086092-A1

Title: Medical diagnostic imaging apparatus, medical image display apparatus, and medical image display method

Description:
FIELD 
     An exemplary embodiment of the present invention relates to a medical diagnostic imaging apparatus, medical image display apparatus, and medical image display method. 
     BACKGROUND 
     Acquisition of medical images with a medical diagnostic imaging apparatus (hereinafter referred to as a modality apparatus) used in medical scenes allows a diagnosis to be made by watching internal parts of the body without damaging the body, and is thus an indispensable technology in modern medical care. Along with advances and performance improvements of the modality apparatus, a wide variety of modality apparatus have been developed according to various body sites and disease detection measures. Furthermore, along with advancement in digitalization of medical images and development of PACS (Picture Archiving and Communication Systems) and HIS (Hospital Information System), an environment surrounding medical care has increasingly been computerized. As a result, medical images acquired by modality apparatus have also come to be converted into electronic data. 
     On the other hand, with diversification of modality apparatus and diversification of imaging methods, different operations and inputs have come to be required of users depending on the modality apparatus and imaging method. Consequently, operations used to enter various settings in the modality apparatus have become complicated. In addition, one examination is often made up of a combination of plural units of imaging (hereinafter referred to as imaging protocols) which use different imaging methods, and it is a heavy burden for the user to make the settings manually with respect to all the imaging protocols. 
     Thus, medical diagnostic imaging apparatus have been provided which reduce operational burden on the user by distinguishing between operations which can be automated and operations which require user inputs, based on purposes of examination as well as on imaging conditions and the like and thereby controlling progress of the entire examination. 
     As mentioned above, with diversification of modality apparatus and diversification of imaging methods, applications used to process acquired medical image data have been diversified as well. For example, processing methods for medical image data acquired by a magnetic resonance imaging (MRI) apparatus include an image processing method known as diffusion tensor imaging (DTI), and an application for creating DTI images is provided. Similarly, applications are available including an application of functional MRI (fMRI) used to observe regional cerebral blood flow produced by brain activity, an application for generating three-dimensional images using a multiplanar reconstruction (MPR) method which involves acquiring arbitrary cross sections from three-dimensional image data or a rendering method which involves creating a projected display on a two-dimensional plane so as to give a three-dimensional appearance, a magnetic resonance spectroscopy (MRS) application capable of capturing chemical information in a living body using a frequency difference known as a chemical shift between MR signals, and an application based on an imaging method such as contrast radiography or cardiac-gated scanning. 
     In order to perform image processing using these applications, it is necessary to properly select medical image data available for use by the respective applications. DTI image is obtained by tensor analysis of a diffusion weighted image (DWI) with enhanced diffusion effect whereby particles such as water molecules in a nerve fiber scatter due to Brownian motion caused by heat. For example, a DWI can be acquired by an imaging method which applies a strong gradient magnetic field known as MPG (Motion Probing Gradient) pulses and thereby enhances a phase shift caused by movements of an imaged object. Also, in order to generate three-dimensional images using the MPR method which involves acquiring arbitrary cross sections from three-dimensional image data or using the rendering method, it is necessary to be compatible with a data format of a three-dimensional volume data obtained by a three-dimensional imaging technique or multi-slice imaging. In this way, the imaging method, format, and the like of image data to be processed varies with the type of application. 
     Also, one examination is made up of plural imaging protocols differing in the imaging method. One or more images are acquired based on one imaging protocol. Hereinafter, data made up of one or more images acquired based on one imaging protocol will be referred to as an image dataset. Thus, the data acquired by one examination (hereinafter referred to as examination data) is a collection of image datasets generated based on respective ones of plural imaging protocols. Therefore, when acquired examination data is subjected to image processing on a medical diagnostic imaging apparatus, it is necessary to select an application compatible with an image dataset selected from the plural image datasets making up the acquired examination data. To start an application, it is necessary to select an image dataset from an image selection screen which lists the plural image datasets and then select an application from an application selection screen which displays a list of applications. In so doing, if the selected image dataset is not available for use by the selected application, the application cannot be started successfully. This creates a task of searching for another application or a task of selecting another image dataset anew on a screen for use to confirm an image dataset. 
     In this way, it is difficult for the user to achieve a suitable combination by selecting an appropriate application from various applications for each of the plural image datasets acquired by plural imaging methods. 
     Thus, there is demand for a medical diagnostic imaging apparatus having a function to help select the right combinations of image datasets and applications. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       In the accompanying drawings: 
         FIG. 1  is a conceptual configuration diagram showing an example of a medical diagnostic imaging apparatus according to the exemplary embodiment; 
         FIG. 2  is a functional block diagram showing a functional configuration example of the medical diagnostic imaging apparatus  1  according to the exemplary embodiment; 
         FIG. 3  is a diagram illustrating an examination and imaging protocols; 
         FIG. 4  is a diagram schematically illustrating examination data and image datasets; 
         FIG. 5  is a flowchart describing application startup on a conventional medical diagnostic imaging apparatus; 
         FIG. 6  is a diagram illustrating an image selection screen displayed on the conventional medical diagnostic imaging apparatus; 
         FIG. 7  is a diagram illustrating the application selection screen displayed on the conventional medical diagnostic imaging apparatus; 
         FIG. 8  is a flowchart showing the first embodiment of the medical diagnostic imaging apparatus according to the exemplary embodiment; 
         FIG. 9  is a diagram illustrating a display example of an image dataset list on the medical diagnostic imaging apparatus according to the exemplary embodiment; 
         FIG. 10  is a diagram illustrating an example of the adaptability assessment table of the medical diagnostic imaging apparatus according to the exemplary embodiment; 
         FIG. 11  is a diagram illustrating an example of the adaptive application list display section of the medical diagnostic imaging apparatus according to the exemplary embodiment; 
         FIG. 12  is a diagram illustrating a first display example of the application processing history display section on the medical diagnostic imaging apparatus according to the exemplary embodiment; 
         FIG. 13  is a diagram illustrating a second display example of the application processing history display section on the medical diagnostic imaging apparatus according to the exemplary embodiment; 
         FIG. 14  is a diagram illustrating resumption of image processing on the medical diagnostic imaging apparatus according to the exemplary embodiment; 
         FIG. 15  is a flowchart showing the second embodiment of the medical diagnostic imaging apparatus according to the present exemplary embodiment; 
         FIG. 16  is a diagram illustrating an example of the adaptive image dataset list display section of the medical diagnostic imaging apparatus according to the exemplary embodiment; 
         FIG. 17  is a diagram illustrating an example of the image dataset history display section of the medical diagnostic imaging apparatus according to the exemplary embodiment; and 
         FIG. 18  is a conceptual configuration diagram showing an example of the medical image display apparatus according to the exemplary embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     To solve the above-described problems, a medical diagnostic imaging apparatus according to the present embodiment includes: an execution unit configured to execute a plurality of imaging protocols included in an examination; and a display control unit configured to display a first screen and a second screen, where the first screen selectably displays a plurality of image datasets collected based on the respective imaging protocols after execution of the plurality of imaging protocols as well as extracts and displays postprocessing applications applicable to individual ones of the image datasets while the second screen is brought up by transitioning from the first screen and used to perform postprocessing of the image datasets, wherein when an application associated with a predetermined image dataset is selected on the first screen, the display control unit starts the selected application and transitions from the first screen to the second screen to perform postprocessing of the predetermined image dataset. 
     A medical diagnostic imaging apparatus, medical image display apparatus, and medical image display method according to an exemplary embodiment of the present invention will be described with reference to the accompanying drawings. 
     (1) Configuration 
       FIG. 1  is a conceptual configuration diagram showing an example of a medical diagnostic imaging apparatus  1  according to the exemplary embodiment. In the example of  FIG. 1 , it is assumed that the medical diagnostic imaging apparatus  1  is an MRI apparatus. The medical diagnostic imaging apparatus  1  according to the present exemplary embodiment is not limited to the MRI apparatus, and may be another modality apparatus such as an X-ray CT (Computed Tomography) apparatus, SPECT (Single Photon Emission computed Tomography) apparatus or PET (Positron Emission computed Tomography) apparatus. As shown in  FIG. 1 , the medical diagnostic imaging apparatus  1  includes an imaging system  11  and a display control unit  12 . 
     The imaging system  11  includes a static magnet  121 , a gradient coil  122 , a gradient power supply  123 , a bed  124 , a bed control unit  125 , a transmitter coil  126 , a transmitter unit  127 , receiver coils  128   a  to  128   e , a receiver unit  129 , and an execution unit (sequence controller)  130 . 
     The static magnet  121  is formed into a hollow cylindrical shape in outermost part of a gantry (not shown) and configured to generate a uniform static magnetic field in an internal space. As the static magnet  121 , a permanent magnet or superconductive magnet is used, for example. 
     The gradient coil  122  is formed into a hollow cylindrical shape and is placed on an inner side of the static magnet  121 . The gradient coil  122  is made up of a combination of coils which correspond, respectively, to X, Y, Z axes orthogonal to one another. Being supplied with electric currents individually from the gradient power supply  123 , the three coils generate gradient magnetic fields whose magnetic field intensity change along the X, Y, Z axes, respectively. Note that the Z axis coincides in direction with the static magnetic field. The gradient power supply  123  supplies an electric current to the gradient coil  122  based on pulse sequence execution data sent from the execution unit  130 . 
     The gradient magnetic fields generated by the gradient coil  122  include a readout gradient magnetic field Gr, a phase encoding gradient magnetic field Ge, and a slice selection gradient magnetic field Gs. The readout gradient magnetic field Gr is used to change a frequency of an MR signal according to spatial position. The phase encoding gradient magnetic field Ge is used to change a phase of the MR signal according to the spatial position. The slice selection gradient magnetic field Gs is used to determine an imaging section as desired. For example, in order to acquire a slice of an axial section, the X, Y, Z axes shown in  FIG. 1  are brought into correspondence with the readout gradient magnetic field Gr, phase encoding gradient magnetic field Ge, and slice selection gradient magnetic field Gs, respectively. 
     The bed  124  includes a table top  124   a  on which a patient P is mounted. The bed  124  inserts the table top  124   a  with the patient P mounted thereon into a cavity (imaging port) of the gradient coil  122  under the control of the bed control unit  125  described later. Normally, the bed  124  is installed such that a longitudinal direction thereof will be parallel to a center axis of the static magnet  121 . 
     The bed control unit  125  moves the table top  124   a  in longitudinal and vertical directions by driving the bed  124  under the control of the execution unit  130 . 
     The transmitter coil  126 , which is placed on an inner side of the gradient coil  122 , generates an RF magnetic field by being supplied with a radio-frequency (RF) signal from the transmitter unit  127 . The transmitter coil  126 , which is also called a whole body RF coil, is also used as a receiver coil. 
     The transmitter unit  127  transmits an RF signal corresponding to Larmor frequency to the transmitter coil  126  based on the pulse sequence execution data sent from the execution unit  130 . 
     The receiver coils  128   a  to  128   e , which are placed on the inner side of the gradient coil  122 , receive MR signals emitted from the patient P in response to the RF signal. Each of the receiver coils  128   a  to  128   e  is an array coil made up of plural coil elements which receive the respective MR signals emitted from the patient P and outputs the received MR signals to the receiver unit  129  when the MR signals are received by respective coil elements. 
     The receiver coil  128   a  is a head coil mounted around the head of patient P. Also, the receiver coils  128   b  and  128   c  are spine coils placed between the spine of the patient P and the table top  124   a . Also, the receiver coils  128   d  and  128   e  are abdominal coils mounted above the abdomen of the patient P. Also, the medical diagnostic imaging apparatus  1  may be equipped with a combined transmitter-receiver coil. 
     The receiver unit  129  generates MR signal data based on the pulse sequence execution data sent from the execution unit  130  as well as on the MR signals outputted from the receiver coils  128   a  to  128   e . Also, upon generating the MR signal data, the receiver unit  129  transmits the MR signal data to the display control unit  12  via the execution unit  130 . 
     Note that the receiver unit  129  has plural receiver channels to receive the MR signals outputted from the plural coil elements of the receiver coils  128   a  to  128   e . When informed by the display control unit  12  about the coil elements used for imaging, the receiver unit  129  assigns receiver channels to the coil elements the receiver unit  129  is informed of, so as to receive the MR signals outputted from the coil elements the receiver unit  129  is informed of. 
     The execution unit  130  is connected with the gradient power supply  123 , bed control unit  125 , transmitter unit  127 , receiver unit  129 , and display control unit  12 . The execution unit  130  includes a processor (not shown) such as a CPU (central processing unit) and memory, and stores control information needed to drive the gradient power supply  123 , bed control unit  125 , transmitter unit  127 , and receiver unit  129 , including, for example, sequence information describing operational control information such as intensity, application duration, and application timing of a pulsed current to be applied to the gradient power supply  123 . 
     Also, the execution unit  130  executes plural imaging protocols included in an examination. The execution unit  130  drives the gradient power supply  123 , transmitter unit  127 , and receiver unit  129  according to stored predetermined sequence information and thereby generates X-axis gradient magnetic field Gx, Y-axis gradient magnetic field Gy, and Z-axis gradient magnetic field Gz as well as HF signals in the gantry. Furthermore, the execution unit  130  drives the bed control unit  125  according to stored predetermined sequence information and thereby moves the table top  124   a  forward and backward in a Z direction with respect to the gantry. 
     The display control unit  12  displays a first screen and second screen, where the first screen selectably displays plural image datasets collected based on the respective imaging protocols after execution of the plural imaging protocols as well as extracts and displays postprocessing applications applicable to individual image datasets while the second screen is brought up by transitioning from the first screen and used to perform postprocessing of the image datasets. Also, in addition to display control of image datasets such as described above, the display control unit  12  performs overall control of the medical diagnostic imaging apparatus  1 , data collection, image reconstruction, and so on. The display control unit  12  includes a communications control unit  10 , a storage unit  20 , a main control unit  30 , a display unit  40 , and an input unit  50 . 
     The communications control unit  10  is connected to the gradient power supply  123 , bed control unit  125 , transmitter unit  127 , and receiver unit  129  of the imaging system  11  via the execution unit  130  and adapted to control input and output of signals exchanged between the connected components and the display control unit  12 . 
     The MR signal data received from the receiver unit  129  is stored in the storage unit  20  via the communications control unit  10 . By performing postprocessing of the MR signal data stored in the storage unit  20 , spectrum data or an image dataset of a desired nuclear spin in the patient P is generated. Applications for use to postprocess the acquired MR signals are available in various types according to the imaging methods such as DWI, MPR, MRS, and fMRI. Such applications run when a program stored in the storage unit  20  is executed by the main control unit  30 . 
     The storage unit  20  stores collected MR signal data, generated image datasets, or plural applications. 
     As a program stored in the storage unit  20  is executed by the main control unit  30 , acquired examination data and applications are selected. 
     The storage unit  20 , which is made up of storage media such as a RAM and ROM, may be configured to include a storage medium, such as a magnetic or optical storage medium or a semiconductor memory, readable by the main control unit  30  and download some or all of programs and data onto these storage media via an electronic network. Also, the applications used by the medical diagnostic imaging apparatus  1  may be prestored in the storage unit  20  or may be acquired from an external application server via the communications control unit  10 . 
     The display unit  40 , which is a typical display device such as a liquid crystal display or OLED (Organic Light Emitting Diode) display, displays images under the control of the main control unit  30 . 
     The input unit  50  is made up of typical input devices such as a keyboard, touch panel, numerical keypad, and/or mouse. The input unit  50  outputs an input signal corresponding to a user action such as selection of an application or image dataset, interruption of an application, or the like to the main control unit  30 . 
       FIG. 2  is a functional block diagram showing a functional configuration example of the medical diagnostic imaging apparatus  1  according to the exemplary embodiment. As shown in  FIG. 2 , the display control unit  12  includes an application storage unit  21 , a start data storage unit  22 , a data input unit  31 , a first list creation unit  32 , an extraction unit  33 , a second list creation unit  34 , a starting unit  35 , an application processing history creation unit  36 , an image dataset history creation unit  37 , an image dataset list display section  41 , an application list display section  42 , an application processing history display section  43 , an image dataset history display section  44 , an adaptive image dataset list display section  45 , an adaptive application list display section  46 , and an input unit  50 . Of these, the data input unit  31 , first list creation unit  32 , extraction unit  33 , second list creation unit  34 , starting unit  35 , application processing history creation unit  36 , and image dataset history creation unit  37  are functions implemented when a program stored in the storage unit  20  is executed by the main control unit  30 . 
     The application storage unit  21  stores image processing applications available for use on a medical diagnostic imaging apparatus  1 . 
     The data input unit  31  acquires examination data from an imaging unit  11 . The examination data includes patient information about the patient who is examined, a name of a modality apparatus used for the examination, and plural image datasets acquired based on plural imaging protocols of the examination. The examination data will be described later. 
     The first list creation unit  32  creates one of two types of list: a list of plural image datasets contained in the examination data and a list of plural applications available for use by the medical diagnostic imaging apparatus  1 . The first list creation unit  32  creates a list of the plural image datasets making up the examination data when an Image Selection Screen is displayed on the medical diagnostic imaging apparatus  1 , and creates a list of the plural applications available for use on the medical diagnostic imaging apparatus  1  when an Application Selection Screen is displayed. 
     The image dataset list display section  41  displays a list of plural image datasets, allowing one image dataset to be selected from the list of plural image datasets. The image dataset list display section  41  displays a list of the plural image datasets making up the examination data when the list is created by the first list creation unit  32 . The list of image datasets created by the first list creation unit  32  will be described later. 
     The application list display section  42  displays a list of plural applications, allowing one application to be selected from the list of plural applications. The application list display section  42  displays a list of the applications available for use on the medical diagnostic imaging apparatus  1  as the list is created by the first list creation unit  32 . The list created by the first list creation unit  32  and containing the applications available for use on the medical diagnostic imaging apparatus  1  will be described later. 
     From plural applications, the extraction unit  33  extracts one or more adaptive applications capable of processing one image dataset selected from image datasets. By comparing accompanying information on examination data with an adaptability assessment table stored in the application storage unit  21 , the extraction unit  33  extracts items for a second list. The second list is created based on the plural image datasets contained in the examination data or applications available for use by the medical diagnostic imaging apparatus  1 , whichever are not selected in creating a first list. That is, if the first list is a list of the plural image datasets contained in the examination data, the second list is created based on the applications available for use on the medical diagnostic imaging apparatus  1 . On the other hand, if the first list is a list of the applications available for use on the medical diagnostic imaging apparatus  1 , the second list is created based on the plural image datasets contained in the examination data. A method used by the extraction unit  33  to extract items for the second list using the adaptability assessment table will be described later. 
     The second list creation unit  34  creates the second list using the items extracted by the extraction unit  33 . When image datasets are extracted by the extraction unit  33 , a list of adaptive image datasets is created, and when applications are extracted, a list of adaptive applications is created. 
     The adaptive image dataset list display section  45  displays a list of one or more adaptive image datasets, allowing one adaptive image dataset to be selected from the list of one or more adaptive image datasets. The adaptive image dataset list display section  45  displays the list of adaptive image datasets, which is a second list created by the second list creation unit  34 . 
     The adaptive application list display section  46  displays a list of one or more adaptive applications, allowing one adaptive application to be selected from the list of one or more adaptive applications. The adaptive application list display section  46  displays the list of adaptive applications, which is a second list created by the second list creation unit  34 . 
     Based on input from the input unit  50  and the like, the starting unit  35  starts an image processing application using a combination of the image dataset and application selected from the first list and second list. 
     The start data storage unit  22  stores a combination of an application and an image dataset, the combination being used to start the application when image processing by the application is interrupted. Besides, the start data storage unit  22  also stores start data generated when the application is started. The start data will be described later. 
     The application processing history creation unit  36  creates an application processing history. The application processing history creation unit  36  creates a display image related to a usage history of applications used for an image dataset. The application processing history creation unit  36  creates the display image of the application processing history based on the application processing history contained in the accompanying information on each image dataset. 
     The application processing history display section  43  displays the application processing history. The application processing history display section  43  displays the display image of the application processing history created by the application processing history creation unit  36 . 
     The image dataset history creation unit  37  creates a usage history of image datasets, based on a history of the image datasets processed by each application. 
     The image dataset history display section  44  displays the image dataset history. The image dataset history display section  44  displays a display image of the image dataset history created by the image dataset history creation unit  37 . 
     (2) Operation 
     First, the examination data and image datasets used by the medical diagnostic imaging apparatus  1  will be described. 
       FIG. 3  is a diagram illustrating an examination and imaging protocols. As shown in  FIG. 3 , one examination is made up of plural imaging protocols.  FIG. 3  shows an example in which one examination is made up of six imaging protocols. 
     The examination shown in the example of  FIG. 3  is made up of six imaging protocols which, in order from left to right, are: “3 Axis Locator” (imaging protocol  1000 ) which involves carrying out imaging to acquire one positioning image each in an X-direction, Y-direction, and Z-direction, “Map” (imaging protocol  2000 ) which involves carrying out imaging to acquire a sensitivity map of a receiving coil, “TOF” (imaging protocol  3000 ) which involves carrying out imaging by a TOF (Time of Flight) method, “Diffusion” (imaging protocol  4000 ) which involves carrying out imaging to obtain a diffusion tensor image by applying a strong gradient magnetic field known as MPG (Motion Probing Gradient) pulses and thereby enhancing a phase shift caused by movements of an imaged object, and “BOLD” (imaging protocols  5000  and  6000 ) which involves carrying out imaging by a BOLD (Blood Oxygenation Level Dependent) method to observe changes in regional cerebral blood flow produced by brain activity, where the BOLD method detects increases in oxygenated hemoglobin in a relative sense. Imaging protocols  5000  and  6000  involve carrying out imaging under two conditions, respectively, to compare a “rest” condition in which the patient is resting and a “task” condition in which the patient is engaged in some task. 
     In this way, one examination is made up of plural imaging protocols, which differ from one another in the imaging method, and the like. 
       FIG. 4  is a diagram schematically illustrating examination data and image datasets. The examination data shown in  FIG. 4  is an example obtained when the examination shown in  FIG. 3  is conducted. 
     The examination data shown in  FIG. 4  is made up of common accompanying information, imaging protocol-specific accompanying information, and image information in order from left to right. The data acquired by the medical diagnostic imaging apparatus  1  is accompanied by information about an imaging condition, an examination type, and the like in addition to the image datasets. The data acquired by the medical diagnostic imaging apparatus  1  conforms, for example, to the DICOM (Digital Imaging and COmmunication in Medicine) standard. DICOM is a global standard which allows data acquired by different medical diagnostic imaging apparatus  1  to be handled by standardized data formats and communications methods. 
     The common accompanying information contains information common to plural imaging protocols making up the examination data. Specifically, as shown under the common accompanying information in  FIG. 4 , the common accompanying information contains an examination name (examination A), a modality type (MRI) used for the examination, and patient information about the patient (patient X). 
     When the examination shown in  FIG. 3  is conducted, an image dataset including plural images is generated in relation to each imaging protocol executed. Each imaging protocol varies in imaging parameters including imaging method, type of generated image, and imaging condition. This information is stored in the imaging protocol-specific accompanying information. As shown under the accompanying information on imaging protocol  3000  in  FIG. 4 , imaging protocol  3000  is a three-dimensional image made up of plural successive slice images whose imaging method is “TOF” and whose image dataset image type is “3D.” 
     The image information shown after the imaging protocol-specific accompanying information in  FIG. 4  exists for each imaging protocol. For example, imaging protocol-specific accompanying information exists for each of the imaging protocols from imaging protocol  1000  to imaging protocol  6000  shown in  FIG. 4 . Accordingly, an image dataset is generated for each imaging protocol. That is, an image dataset exists for each of the imaging protocols from imaging protocol  1000  to imaging protocol  6000 . 
     (Conventional Embodiment) 
       FIG. 5  is a flowchart describing application startup on a conventional medical diagnostic imaging apparatus. 
     In ST 101 , the examination data described in  FIG. 4  is acquired by a conventional medical diagnostic imaging apparatus. 
     In ST 103 , once the examination data described above is acquired, image datasets are displayed on an image selection screen. 
       FIG. 6  is a diagram illustrating an image selection screen displayed on the conventional medical diagnostic imaging apparatus.  FIG. 6  shows an example of an image selection screen W1 of the conventional medical diagnostic imaging apparatus. In the example shown in  FIG. 6 , Image Selection Screen and Application Selection Screen are displayed switchably in tab display format. When the tab of Application Selection Screen is pressed, an application selection screen W2 is brought up. Although in the example of  FIG. 6 , the display is switched by tabs, a button may be displayed to switch between Image Selection Screen and Application Selection Screen. 
     When the examination illustrated by example in  FIG. 4  is conducted, an image dataset is generated for each of the six imaging protocols. Each of six screen segments on the right of the image selection screen W1 shown in the example of  FIG. 6  displays an image of an image dataset of the examination data and a character string describing an imaging protocol. The images displayed in the six frame segments are an image of “3 Axis Locator” (imaging protocol  1000 ), an image of “Map” (imaging protocol  2000 ), an image of TOF (imaging protocol  3000 ) in order from upper left to upper right; and an image of “Diffusion” (imaging protocol  4000 ), an image of “BOLD (rest)” (imaging protocol  5000 ), and an image of “BOLD (task)” (imaging protocol  6000 ) in order from lower left to lower right. Also, as shown in  FIG. 6 , the frame in which the image dataset of each imaging protocol is displayed also presents an imaging protocol number for use to identify the displayed image and a character string describing the imaging method. 
     Also, the left side of the image selection screen W1 in  FIG. 6  displays the patient information and modality type contained in the common accompanying information on the examination data. Since the examination shown in  FIG. 4  has been conducted using an MRI apparatus, “MRI” is indicated as the modality used. 
     In ST 105  of  FIG. 5 , an image dataset is selected on the image selection screen W1. Based on the display shown in  FIG. 6 , the user selects an image dataset from images of image datasets and character strings describing imaging protocols, using an input unit  50  made up of a mouse and keyboard. 
     In ST 107 , the image selection screen W1 transitions to the application selection screen W2, bringing up the application selection screen W2. The screen transition from the image selection screen W1 to the application selection screen W2 takes place as a tab or button of Application Selection Screen displayed on the image selection screen W1 is pressed by the user via an input unit  50 . 
       FIG. 7  is a diagram illustrating the application selection screen W2 displayed on the conventional medical diagnostic imaging apparatus.  FIG. 7  shows an example of the application selection screen W2 of the conventional medical diagnostic imaging apparatus. As with the example of  FIG. 6 , in  FIG. 7 , Image Selection Screen and Application Selection Screen are displayed switchably in tab display format.  FIG. 7  shows an example of a display after an image dataset of imaging protocol  3000  is selected on the image selection screen W  1  of  FIG. 6  and a transition to the application selection screen W2 takes place. 
     A list of applications is shown on the left side of  FIG. 7 . A “subtraction” application displayed on the upper left of the application list is an application which performs image processing to compare images obtained from a same site and differing in time phase and exclude a structure common to the images. For example, in comparing images before and after angiography, a subtraction process allows only an angiographic signal to be picked up by excluding unnecessary tissues such as bones. Also a “fusion” application shown to the right is designed to perform image processing to display superimposed images. With PET, it is difficult to acquire morphological information on organs and the like. Thus, an image is sometimes observed by being superimposed with an image acquired by another modality apparatus such as an X-ray CT apparatus or MRI apparatus capable of acquiring morphological information. Similarly, a “3D MPR rendering” application displayed to the lower left is used to generate a three-dimensional image by an MPR method or rendering method, where the MPR method is designed to acquire arbitrary cross sections from a three-dimensional image dataset. A “DWI/DTI” application is used to acquire a diffusion tensor image. An “MRS” application is designed to image MR sensitivity of a target nuclide as well as abundance of the nuclide in a living body. An “fMRI” application is used to observe regional cerebral blood flow produced by brain activity. “CT perfusion” and “MRI perfusion” applications are designed to analyze blood flow using images obtained by an X-ray CT apparatus and MRI apparatus, respectively. 
     In addition to the applications described above, the applications shown on the left side of  FIG. 7  include various image processing applications specialized in an anatomical region or imaging method, such as an application for analyzing a cardiac-gated scan. 
     In ST 109  of  FIG. 5 , an application is selected on the application selection screen W2. 
     In ST 111 , it is determined whether the application selected on the application selection screen W2 can be started for the image dataset selected on the image selection screen W1. If the application can be started, the application starts in ST 113 , starting image processing. On the other hand, if it is determined in ST 111  that the combination of the image dataset and application is incompatible, an error results as shown in ST 115  and the application does not start. 
     An image of imaging protocol  3000  selected on the image selection screen W1 of  FIG. 6  is displayed on the right side of  FIG. 7 . As information describing the image of imaging protocol  3000 , the imaging protocol number and a character string “TOF” describing the imaging method are displayed. With the conventional medical diagnostic imaging apparatus, an application displayed on the left side of  FIG. 7  needs to be selected, based on information about the imaging protocol including the displayed character string describing the imaging method. 
     For example, if the “fMRI” application is selected in the example of  FIG. 7 , the application does not start. Because of a difference in the imaging method, fMRI, which uses the BOLD method to analyze an amount of oxygenated hemoglobin changing with brain activity, cannot be used for the image dataset of imaging protocol  3000  acquired by the TOF method. In this way, depending on the difference in the imaging method and the like, there are applications available for use and applications unavailable for use. At startup of each selected application, the conventional medical diagnostic imaging apparatus determines whether an image dataset selected earlier can be used on the application. 
     As described above, with the conventional medical diagnostic imaging apparatus, since image datasets and applications are selected freely by the user, an incompatible combination of an image dataset and application could be selected. In that case, the application does not start successfully, and with the conventional medical diagnostic imaging apparatus, it is necessary to select image dataset and application from the beginning by returning to ST 103 . 
     Furthermore, the conventional medical diagnostic imaging apparatus includes the image selection screen W1 used to select an image dataset and the application selection screen W2 used to select an application, making it necessary to select an image dataset and application separately on the respective screens. Consequently, if a combination of an image dataset and application is incompatible, the application does not start up, and it is necessary to make selections anew by returning to the respective screens. 
     Also, plural imaging protocols are executed in one examination, and plural image datasets are acquired in relation to each imaging protocol. Also, different imaging methods are used for different imaging protocols and the image datasets available for use vary from application to application. Also, since the information which can be displayed on the image selection screen W1 including imaging conditions for image datasets is part of information contained in the accompanying information, the user has to select an application based on limited information. 
     Thus, the present invention provides the medical diagnostic imaging apparatus  1  which assists user selection by creating a list of applications and a list of image datasets based on either the applications or image datasets whichever are selected. 
     In selecting the image datasets and applications, an embodiment in which the image datasets are selected first will be referred to herein as a “first embodiment” and an embodiment in which the applications are selected first will be referred to as a “second embodiment” and these embodiments will be described below. 
     First Embodiment 
     The first embodiment involves selecting image datasets first. 
       FIG. 8  is a flowchart showing the first embodiment of the medical diagnostic imaging apparatus  1  according to the exemplary embodiment. 
     In ST 121 , examination data is inputted to the data input unit  31 . Via the execution unit  130 , the data input unit  31  acquires the MR signals collected by the imaging unit  11 . The examination data acquired by the data input unit  31  is, for example, data in a format shown in  FIG. 4 , and includes accompanying information in addition to images. 
     In ST 123 , the image selection screen W1 is displayed in order for the user to use examination data. 
     In ST 125 , since the displayed screen is the image selection screen W1, the first list creation unit  32  creates a list of image datasets as a first list. The list of image datasets lists all the image datasets contained in the acquired examination data. 
     In ST 127 , the list of image datasets created by the first list creation unit  32  is displayed in the image dataset list display section  41 . 
       FIG. 9  is a diagram illustrating a display example of an image dataset list on the medical diagnostic imaging apparatus  1  according to the exemplary embodiment.  FIG. 9  shows an example in which the image selection screen W1 shown in tab format in  FIG. 6  is displayed as a single screen. A To Application Selection Screen button is provided in the lower left of  FIG. 9 , allowing transition to the application selection screen W2. 
     The left side of the image selection screen W1 in  FIG. 9  displays the examination name and modality type contained in the common accompanying information on the examination data as in the case of  FIG. 6 . 
     The right side of the image selection screen W1 in  FIG. 9  is the image dataset list display section  41 . The image dataset list display section  41  displays a list of image datasets. The list of image datasets lists all the image datasets contained in the examination data. In the example of  FIG. 9 , individual datasets in the list are displayed in respective frames obtained by dividing the image dataset list display section  41  into six parts. Each frame displays an image acquired by one imaging protocol as well as character strings describing the imaging protocol number and an imaging condition. For example, an image based on imaging protocol  1000  (3 Axis locator) is displayed in the upper left frame of the image dataset list display section  41 , and character strings “imaging protocol  1000 ” and “3 Axis locator” describing the image are displayed as well. 
     In ST 129  of  FIG. 8 , based on the display in the image dataset list display section  41 , the user selects an image dataset and the selected information is transmitted to the extraction unit  33  through the input unit  50 . 
     In ST 131 , the extraction unit  33  extracts applications capable of processing the selected image dataset from all the applications stored in the application storage unit  21 . 
       FIG. 10  is a diagram illustrating an example of the adaptability assessment table of the medical diagnostic imaging apparatus  1  according to the exemplary embodiment. As shown in  FIG. 10 , for each application type, the adaptability assessment table prescribes relations with at least “modality type,” “imaging method,” and “image type” of the accompanying information on the image dataset as conditions for starting the application. All or none of the conditions of the accompanying information may be set for each application. An application for which no determination condition is set supports all image datasets. 
     “Modality type” in the adaptability assessment table indicates the type of modality, such as X-ray CT apparatus (CT), MRI apparatus (MRI), or PET, which generates image datasets available for use by the application. “Imaging method” corresponds to the imaging method, such as the TOF method and BOLD method, selected according to a purpose of examination and indicates for which imaging method the application performs image processing. “Image type” indicates the type of supported image, such as a two-dimensional image (2D) and three-dimensional image (3D). Besides, the adaptability assessment table may prescribe “imaging parameters” and the like, which in turn prescribe imaging conditions such as “number of slices,” “slice direction,” and the like. 
     In the example of  FIG. 10 , the “modality type” of the “subtraction” application is “CT/MRI,” meaning that the application can handle image datasets acquired by any of an X-ray CT apparatus and MRI apparatus. It is indicated that “imaging method” is “contrast/noncontract,” meaning that imaging may or may not involve injection of a contrast medium into the patient. “Image type” is “2D/3D,” meaning that both two-dimensional images and three-dimensional images are supported. Also, in the case of the “fusion” application, “modality type” is “CT/MRI/PET,” meaning that the application can handle image datasets acquired by any of an X-ray CT apparatus, MRI apparatus, and PET. “Imaging method” is marked by “-,” meaning that the imaging method does not affect image processing by the application. “Image type” is “2D,” meaning that two-dimensional images are supported. Similarly, in the case of the “3D MPR rendering” application, “modality type” is “CT/MRI,” meaning that the application can handle image datasets acquired by any of an X-ray CT apparatus and MRI apparatus. “Imaging method” is marked by “-,” meaning that the imaging method does not affect image processing by the application. “Image type” is “3D.” In this way, depending on the application, image processing may be limited by the image type. In the case of the “DWI/DTI” application, “modality type” is “MRI,” meaning that the application can use only image datasets acquired by an MRI apparatus. Also, “imaging method” is “Diffusion” and “image type” is “3D.” In the case of the “MRS” application, “modality type” is “MRI,” meaning that the application can process image datasets acquired by an MRI apparatus. Also, “imaging method” is “MRS,” meaning that the application can process image datasets acquired by using a frequency difference known as a chemical shift between MR signals. Also, “image type” is “3D.” In the case of the “fMRI” application, “modality type” is “MRI,” meaning that the application can process image datasets acquired by an MRI apparatus. Also, “imaging method” is “BOLD,” meaning that the application can process image datasets acquired by an imaging method which allows observation of increases and decreases in oxygenated hemoglobin. Also, “image type” is “3D.” In the case of the “CT perfusion” application, “modality type” is “CT,” meaning that the application can process image datasets acquired by an X-ray CT apparatus. On the other hand, in the case of the “MRI perfusion” application, “modality type” is “MRI,” meaning that the application can process image datasets acquired by an MRI apparatus. The “imaging method” of “CT perfusion” and “MRI perfusion” is “contrast,” meaning that imaging involves injection of a contrast medium into the patient. 
     The adaptability assessment table illustrated by example in  FIG. 10  prescribes essential determination conditions which must be complied with, but any desired determination conditions may also be prescribed. Conversely, a condition which disables any image dataset provided therewith from starting may be prescribed. The adaptability assessment table shown in  FIG. 10  is an example of a table which is common to various modality apparatus, but an adaptability assessment table may be provided for each medical diagnostic imaging apparatus used. 
     The extraction unit  33  acquires “imaging method” and “image type” from the individual accompanying information on the selected image dataset and acquires “modality type” from the common accompanying information on the examination data to which the image dataset belongs. Then, based on the adaptability assessment table, an application capable of processing the selected image dataset is extracted. 
     In ST 133  of  FIG. 8 , the second list creation unit  34  creates a list of adaptive applications as a second list based on the applications extracted by the extraction unit  33 . 
     In ST 135 , since the list created by the second list creation unit  34  is a list of adaptive applications, the list is displayed in the adaptive application list display section  46 . 
     In this way, according to the first embodiment, one image dataset is selected first from all the image datasets contained in the examination data. The extraction unit  33  extracts a list of applications capable of processing the selected image dataset from the applications stored in the application storage unit  21 . Then, based on the extracted applications, the second list creation unit  34  creates and displays a list of adaptive applications. 
       FIG. 11  is a diagram illustrating an example of the adaptive application list display section  46  of the medical diagnostic imaging apparatus  1  according to the exemplary embodiment.  FIG. 11  shows part of the image selection screen W1 shown in  FIG. 9 . In  FIG. 11 , as in the case of  FIG. 9 , a list of image datasets is displayed in the image dataset list display section  41  on the right side of the image selection screen W1, and in the example shown in  FIG. 11 , imaging protocol  3000  is selected. Information that the image dataset of imaging protocol  3000  has been selected is acquired and transmitted to the extraction unit  33 , for example, when an input operation such as a press on a display location of an imaging protocol image of imaging protocol  3000  is performed via the input unit  50 . 
     As illustrated by example in  FIG. 4 , it is assumed that the image dataset of imaging protocol  3000  contains individual accompanying information which specifies that “imaging method” is “TOF” and that “image type” is “3D.” Furthermore, it is assumed that the common accompanying information on the examination data to which imaging protocol  3000  belongs contains “MRI” as “modality type.” Under these conditions, the extraction unit  33  extracts two types of applications—“subtraction” and “3D MPR/rendering”—from the application storage unit  21  based on the adaptability assessment table shown in  FIG. 10 . 
     A list of adaptive applications is created from the extracted applications by the second list creation unit  34  and displayed in the adaptive application list display section  46 . As shown in  FIG. 11 , the list of adaptive applications lists two applications: “subtraction” and “3D MPR/rendering.” The list of adaptive applications is displayed in the adaptive application list display section  46  on imaging protocol  3000  selected. Also, the adaptive application display section  46  may be popped up on the image selection screen. 
     In ST 137  of  FIG. 8 , one application is selected by the user from the list of adaptive applications displayed in the adaptive application display section  46 . Information about the selected application is transmitted to the starting unit  35  via the input unit  50 . 
     In ST 139 , the starting unit  35  generates start data from the selected application and selected image dataset and stores the start data in the start data storage unit  22 . The start data contains information about a combination of the image dataset selected from the list of image datasets and the application selected from the list of adaptive applications, where the list of image datasets is a first list while the list of adaptive applications is a second list. As in the case of other image datasets, the start data may be stored as part of the examination data or may be stored in the storage unit  20 . 
     In ST 141 , the starting unit  35  starts an image processing application using the image dataset selected from the list of image datasets, i.e., the first list, and the application selected from the list of adaptive applications, i.e., the second list. 
     In this way, whereas conventionally an application cannot be started without transitioning from the image selection screen W1 to the application selection screen W2, in the first embodiment, an application can be started directly on the image selection screen W1 displayed first. Furthermore, since only the applications which can use the selected image dataset are configured to be selectable, applications which cannot use the selected image dataset are not selected, and thus it is possible to avoid errors during startup. This eliminates the need to switch between the image selection screen W1 and application selection screen W2 which is the case with the conventional medical diagnostic imaging apparatus, and thereby simplifies user operation. 
     As a variation of the first embodiment, description will be given of an example in which the application processing history display section  43  is displayed together with the list of adaptive applications displayed in the adaptive application display section  46 . A display image of an application processing history is created by the application processing history creation unit  36  based on the application processing history contained in the accompanying information on the image dataset, where the application processing history concerns the applications used in the past. The application processing history display section  43  displays the applications which have ever processed the selected image dataset. 
       FIG. 12  is a diagram illustrating a first display example of the application processing history display section  43  on the medical diagnostic imaging apparatus  1  according to the exemplary embodiment. As with  FIG. 11 ,  FIG. 12  shows part of the image selection screen W1 shown in  FIG. 9 . Furthermore, in the example of  FIG. 12 , the image dataset of imaging protocol  3000  has been selected as in the case of  FIG. 11 . Also, a list of adaptive applications compatible with the image dataset of imaging protocol  3000  is displayed as in the case of  FIG. 11 . A difference from  FIG. 11  lies in that the application processing history display section  43  displayed on a side of the adaptive application list contains a checkmark. The checkmark indicates an application which has ever been used for the image dataset of imaging protocol  3000 . That is, past results indicate that the “subtraction” application can be started using the image dataset of imaging protocol  3000 . 
     In this way, when the image dataset of imaging protocol  3000  is selected, not only a list of adaptive applications, but also the application processing history display section  43  is displayed at the same time, making it possible to select an application which has ever been started using the selected image dataset, and thereby start the application reliably. 
     The display image of the application processing history displayed in the application processing history display section  43  described above is created based on the application processing history. The application processing history is stored in the application storage unit  21  or the storage unit  20  in a form which allows reference and is updated as appropriate each time the application is started. 
       FIG. 13  is a diagram illustrating a second display example of the application processing history display section  43  on the medical diagnostic imaging apparatus  1  according to the exemplary embodiment. As with  FIG. 11 ,  FIG. 13  shows part of the image selection screen W1 shown in  FIG. 9 . 
       FIG. 12  above shows an example in which an image dataset is selected on the image selection screen W1 and the application processing history display section  43  is displayed simultaneously with a list of adaptive applications.  FIG. 13  shows an example in which when a list of image datasets is displayed on the image selection screen W1, the image dataset list display section  41  and application processing history display section  43  are displayed at the same time. As with the example of  FIG. 12 ,  FIG. 13  shows an example in which the image dataset of imaging protocol  3000  has already been subjected to image processing by the “subtraction” application. Whereas in  FIG. 12 , such an application processing history is marked with a checkmark, in the example shown in  FIG. 13 , a character string which indicates a name of an application is displayed on the image dataset of imaging protocol  3000 . In the example shown in  FIG. 13 , when the image dataset of imaging protocol  3000  is selected in this state, a list of adaptive applications is displayed. The list of adaptive applications displayed in  FIG. 13  is identical to the list in  FIG. 11 . 
     In this way, as the image dataset and application processing history are displayed simultaneously, it is possible to select an application which has ever been started using the selected image dataset. 
     Also, although  FIGS. 12 and 13  show examples of displaying a history of applications which have ever been used for a selected image dataset, the application processing history display section  43  may display a history of applications which have ever been used for other image datasets or other examination data. For example, a history of applications used for image datasets of other examination data acquired by a same imaging method as the selected image dataset may be displayed in the application processing history display section  43 . 
     Such a display allows the user to select which application to use for the selected image dataset, making it possible to select the application easily. 
     Furthermore, with the medical diagnostic imaging apparatus  1  according to the present exemplary embodiment, when image processing is interrupted, the interrupted process can be resumed. With the conventional medical diagnostic imaging apparatus, to resume an application in case of such interruption handling, it is necessary to select an image dataset on the image selection screen W1 again, transition to the application selection screen W2, and select an application. On the other hand, according to the present exemplary embodiment, since start data is generated and stored in the start data storage unit  22  when an application is started, the application can be resumed easily using the start data. For example, the start data may be associated with the image dataset processed halfway by the application. Also, a process run by the application may be stored by being associated with the pre-process image dataset, and when the application is resumed using the start data, the stored process may be performed on the image dataset. Also, the start data may be designed to be able to reproduce not only the process performed on the image dataset by the application, but also a display and the like existing at a time of the interruption. For example, a state of tab and button display at the time of the interruption may be stored as start data, allowing the display at the time of the interruption to be reproduced. 
     Furthermore, the start data may be associated with information other than imaging conditions used in application processes and the image datasets acquired at a time of imaging. Also, the start data may be generated not only upon an interruption of the application, but also before initial startup (before selection of the application). For example, in an fMRI examination, information about a task and state of the patient is recorded simultaneously with MR signals from the patient. An fMRI application performs image processing using information about a task, state, and the like of the patient during imaging. In the case of such an application, it is apparent that the application uses data such as one described above. Thus, the start data may be generated in advance before the initial startup of the application by combining image datasets with the imaging conditions used for the application, imaging-time information, and the like. Also, even at a time of initial startup, if start data already exists, the user may be allowed to start the application by simply selecting the start data. 
       FIG. 14  is a diagram illustrating resumption of image processing on the medical diagnostic imaging apparatus  1  according to the exemplary embodiment. There are cases where an application interruption request is entered via the input unit  50  or the like.  FIG. 14  is an example of resuming a process performed by the “subtraction” application with respect to the image dataset of imaging protocol  3000 . “Start data  1000 ” generated based on the image dataset of imaging protocol  3000  is displayed in  FIG. 14 . A name which uniquely identifies the start data is given to the start data using the order in which, or date on which, the start data is generated. 
     Also, as described above, the start data is a collection of information on a selected image dataset and selected application. Thus, the imaging protocol number and imaging conditions of the image dataset serving as a basis of the start data may be displayed as well. In the example of  FIG. 14 , which shows “start data  1000 ” presented when the “subtraction” application is selected for the image dataset of imaging protocol  3000 , character strings of “imaging protocol  3000 ” and “TOF” are displayed in a frame in which “start data  1000 ” is displayed. 
     Start data  1000  may be displayed in the image dataset list display section  41 . Also, when displayed in the image dataset list display section  41 , start data  1000  may be displayed alone or together with other image datasets. In the example of  FIG. 14 , start data  1000  is displayed together with other image datasets. 
     In the example of  FIG. 14 , a name of a currently running application as well as a Resume button used to resume the application are displayed in the frame where start data  1000  is displayed. When the Resume button is pressed, the application is resumed by the starting unit  35  based on start data  1000 . 
     In this way, use of start data to resume an application makes it possible to avoid switching between the image selection screen W1 and application selection screen W2 which is the case with the conventional medical diagnostic imaging apparatus, and thereby resume the application easily. 
     Second Embodiment 
     The second embodiment involves fist selecting an application to be used. 
       FIG. 15  is a flowchart showing the second embodiment of the medical diagnostic imaging apparatus  1  according to the present exemplary embodiment. The same steps as those in the first embodiment shown in  FIG. 8  are denoted by the same step numbers as the corresponding steps in  FIG. 8 . 
     In ST 121 , the data input unit  31  acquires examination data. 
     In ST 151 , the user displays the application selection screen W2. 
     In ST 153 , the first list creation unit  32  creates a list of all applications stored in the application storage unit  21 . As described in the first embodiment, the first list creation unit  32  determines which is the displayed screen and creates a list of applications if the displayed screen is the application selection screen W2. 
     In ST 155 , the list of applications created by the first list creation unit  32  is displayed in the application list display section  43 . 
     In ST 157 , the user selects an application based on the display in the application list display section  43 . The application is selected through input via the input unit  50  made up of a mouse and keyboard. 
     In ST 159 , based on the adaptability assessment table, the extraction unit  33  extracts image datasets available for use by the selected application. The extraction unit  33  extracts an image dataset by comparing items related to the accompanying information set in the adaptability assessment table of the selected application, the common accompanying information contained in the examination data, and the individual accompanying information on all the image datasets with one another. Based on the image dataset extracted by the extraction unit  33 , the second list creation unit  34  creates a list of adaptive image datasets. 
     In ST 161 , the list of adaptive image datasets is displayed in the adaptive image dataset list display section  45 . 
       FIG. 16  is a diagram illustrating an example of the adaptive image dataset list display section  45  of the medical diagnostic imaging apparatus  1  according to the exemplary embodiment. In the example shown in  FIG. 16 , the application selection screen W2 illustrated by example in  FIG. 7  is displayed as a single screen. A To Image Selection Screen button is provided in the lower left of  FIG. 16 , allowing transition to the image selection screen W1. 
     In the example of  FIG. 16 , the “fMRI” application selected is indicated by hatching. Once an application is selected on the application selection screen W2, the extraction unit  33  extracts image datasets available for use by the selected application from the acquired examination data. As can be seen from the “fMRI” row of the adaptability assessment table shown in  FIG. 10 , in the accompanying information on available image datasets, “modality type” is “MRI” and the imaging method is the “BOLD” method. The extraction unit  33  extracts the image datasets whose imaging method is the “BOLD” method, based on the fact that the common accompanying information on the acquired examination data indicates that the modality type used is “MRI” as well as on the individual accompanying information on the image dataset. Thus, the extraction unit  33  extracts imaging protocols  5000  and  6000  whose image datasets are available for use by the “fMRI” application. A list made up of imaging protocols  5000  and  6000  is the list of adaptive image datasets. 
     As shown on the right side of  FIG. 16 , the image datasets of imaging protocols  5000  and  6000  are displayed in the adaptive image dataset list display section  45  of the application selection screen W1. 
     In ST 163  of  FIG. 15 , one image dataset is selected from the list of adaptive image datasets displayed in the adaptive image dataset list display section  45 , and the selected information is transmitted to the starting unit  35  via the input unit  50 . 
     In ST 139 , start data is created by the starting unit  35  and stored in the start data storage unit  22 . 
     In ST 141 , the starting unit  35  starts the application using the application selected from the list of applications and the image dataset selected from the list of adaptive image datasets, where the list of applications is a first list and the list of adaptive image datasets is a second list. 
     In this way, if the image datasets available for use by the application selected on the application selection screen W2 are extracted and displayed in the adaptive image dataset list display section  45 , the application can be started directly from the application selection screen W2. 
     Note that as with the first embodiment, according to the second embodiment, in case of application interruption handling, image processing can be resumed using the start data. 
     Also, as with the first embodiment, according to a variation, a history of image datasets which have ever been processed by the application can be displayed. 
       FIG. 17  is a diagram illustrating an example of the image dataset history display section  44  of the medical diagnostic imaging apparatus  1  according to the exemplary embodiment.  FIG. 17  shows the application selection screen W2 as in the case of  FIG. 16 . In  FIG. 17 , applications are listed on the left side and a list of adaptive image datasets is displayed in the adaptive image dataset list display section  45  on the right side. A display of an image dataset history is created by the image dataset history creation unit  37 . In the example of  FIG. 17 , as with the example of  FIG. 16 , the “fMRI” application is selected and the image datasets of imaging protocols  5000  and  6000  available for use by the “fMRI” application are displayed in the adaptive image dataset list display section  45 . In the example shown in  FIG. 17 , imaging protocol  5000  has already been processed by the “fMRI” application. 
     In the example of  FIG. 17 , the image dataset history display section  44  is displayed on a side of an “fMRI” application button. The image dataset history display section  44  lists the image datasets already processed by the selected application. In the example of  FIG. 17 , “imaging protocol  5000 ” is shown on a side of the “fMRI” application button, meaning that “imaging protocol  5000 ” has already been processed by the “fMRI” application. Usage histories of the image datasets in each application are stored in the accompanying information on the respective image datasets. 
     Also, the image dataset history display section  44  may display not only the imaging protocol numbers used by the selected application, but also the imaging methods and the like of the image datasets used by the application (not shown). Furthermore, regarding the imaging method display, the imaging methods used by the selected application may be displayed together with other examination data as in the case of the application processing history display section  43  according to the first embodiment. 
     In this way, by displaying a history of the image datasets used by the selected application, it is possible to reliably select an image dataset which can start the selected application. 
     As described above, according to the present invention, an item is selected from a first list, which is one of a list of all image datasets and a list of all applications, and then a second list is created listing items thereof able to be combined with the item selected from the first list. This makes it possible to start the application directly from the screen displayed to perform a first selection an item, without a screen transition from the image selection screen W1 or application selection screen W2. Also, to make a second selection from the list generated based on the first selection, choices in making the second selection are narrowed down in advance. Consequently, startup with an incompatible combination of an image dataset and application is avoided. Also, an image dataset and application can be selected easily. Furthermore, an application can be started from any one of the application selection screen and image selection screen, eliminating the need to switch between screens as is conventionally the case. 
     Furthermore, processes performed by the display control unit  12  of the medical diagnostic imaging apparatus  1  can be performed by an apparatus separate from the medical diagnostic imaging apparatus  1 , e.g., by a medical image display apparatus which reads X-rays and displays X-ray images. 
       FIG. 18  is a conceptual configuration diagram showing an example of the medical image display apparatus  100  according to the exemplary embodiment. As shown in  FIG. 18 , the medical image display apparatus  100  includes the communications control unit  10 , storage unit  20 , main control unit  30 , display unit  40 , and input unit  50 . 
     The medical image display apparatus  100  is connected to a consolidated medical image management server  200  and the medical diagnostic imaging apparatus  1  through an electronic network via the communications control unit  10 . The communications control unit  10  supports various communications protocols according to network configurations. 
     Examples of the medical diagnostic imaging apparatus  1  include various medical diagnostic imaging apparatus such as a general radiographic X-ray apparatus, X-ray CT (Computed Tomography) apparatus, MRI (Magnetic Resonance Imaging) apparatus, PET (Positron Emission Tomography) apparatus, and ultrasound diagnostic apparatus. 
     Examination data acquired by the medical image display apparatus  100  may be any of examination data acquired by the medical diagnostic imaging apparatus  1  including X-ray images taken by a general radiographic X-ray apparatus, multi-slice images taken by an X-ray CT apparatus, MRI apparatus, PET apparatus, and the like, and ultrasound images taken by an ultrasound diagnostic apparatus. 
     When a program stored in the storage unit  20  is executed by the main control unit  30 , postprocessing applications applicable to the image datasets described above are extracted and displayed and the image datasets available for use by a selected application are displayed. Also, the application is started by a combination of a selected image dataset and the application. 
     With the configuration shown in  FIG. 18 , the medical image display apparatus  100  provides advantages similar to those of the medical diagnostic imaging apparatus  1 .