Abstract: A clinical decision support (CDS) system comprises: a case grouping sub-system (10) including a graphical user interface (30) that is operative to simultaneously display data representing a plurality of patient cases and further configured to enable a user to group selected patient cases represented by the simultaneously displayed data into clinically related groups (32) as selected by the user; a probative features determination sub-system (12) that is operative to determine probative features (44) that correlate with the clinically related groups; and a CDS user interface (16) that is operative to receive current patient data relating to a current patient case and to output clinical decision support information based on values of the probative features determined from the received current patient data.

Abstract: When characterizing a tumor or lesion as malignant or benign, a system (10) receives an image of the lesion volume (50), employs a processor (12) to perform a raw segmentation of the image, the results of which are stored to memory (14). Then processor then executes a hole-filling procedure to fill in dark areas in the image of the lesion representing necrotic tissue that absorbed little or no contrast agent, and optionally a leakage removal procedure to remove image voxels associated with non-lesion tissue, e.g., blood vessels, in which the contrast agent was present during imaging, to generate a complete lesion volume. A voxel analyzer (18) assesses a number of voxels included in the raw segmentation of the lesion image, and the final segmentation (e.g., after filling and optional leakage removal). A segmentation comparator (20) computes a ratio of dark area voxels related to necrotic tissue detected after the raw segmentation to total voxels detected in the final image segmentation.

Abstract: A system is provided for automatic selection of medical images. The system comprises an input (302) for receiving a temporal sequence of medical images acquired with a hand-held medical imaging device. An object detector (303) is provided for detecting an object in at least one of the images. An image selector (304) is provided for selecting an image in which the object has been detected by the object detector. A snapshot means (305) is provided for storing the selected image as a snapshot. Moreover, a hand-held medical imaging device is provided for generating the sequence of medical images.

Abstract: A diagnostic system having an image loader including a processor for processing multiple modality images, at least one of the multiple modality images being a mammogram image, the processing including generating diagnostic information based on a computer aided diagnostic tool and an image viewer simultaneously displaying the multiple modality images.

Abstract: A method for tracking creation of a treatment plan for a patient includes obtaining an input indicative of a state of a task in the treatment plan creation workflow and generating a signal indicative of a set of tasks of the treatment plan creation workflow, including the state of the task corresponding to the received input. A system includes a processor (100) that generates a treatment plan for a patient based on a treatment plan creation workflow for the patient, wherein the treatment plan creation work-flow includes one or more tasks to be completed for generating the treatment plan and an apparatus (112, 116 and/or 118) that presents a signal indicative of a state of at least one of the treatment plan or the one or more tasks.

Abstract: A clinical decision support (CDS) system comprises: a case grouping sub-system (10) including a graphical user interface (30) that is operative to simultaneously display data representing a plurality of patient cases and further configured to enable a user to group selected patient cases represented by the simultaneously displayed data into clinically related groups (32) as selected by the user; a probative features determination sub-system (12) that is operative to determine probative features (44) that correlate with the clinically related groups; and a CDS user interface (16) that is operative to receive current patient data relating to a current patient case and to output clinical decision support information based on values of the probative features determined from the received current patient data.

Abstract: When characterizing a tumor or lesion as malignant or benign, a system (10) receives an image of the lesion volume (50), employs a processor (12) to perform a raw segmentation of the image, the results of which are stored to memory (14). Then processor then executes a hole-filling procedure to fill in dark areas in the image of the lesion representing necrotic tissue that absorbed little or no contrast agent, and optionally a leakage removal procedure to remove image voxels associated with non-lesion tissue, e.g., blood vessels, in which the contrast agent was present during imaging, to generate a complete lesion volume. A voxel analyzer (18) assesses a number of voxels included in the raw segmentation of the lesion image, and the final segmentation (e.g., after filling and optional leakage removal). A segmentation comparator (20) computes a ratio of dark area voxels related to necrotic tissue detected after the raw segmentation to total voxels detected in the final image segmentation.

Abstract: A system is provided for automatic selection of medical images. The system comprises an input (302) for receiving a temporal sequence of medical images acquired with a hand-held medical imaging device. An object detector (303) is provided for detecting an object in at least one of the images. An image selector (304) is provided for selecting an image in which the object has been detected by the object detector. A snapshot means (305) is provided for storing the selected image as a snapshot. Moreover, a hand-held medical imaging device is provided for generating the sequence of medical images.

Abstract: A diagnostic system having an image loader including a processor for processing multiple modality images, at least one of the multiple modality images being a mammogram image, the processing including generating diagnostic information based on a computer aided diagnostic tool and an image viewer simultaneously displaying the multiple modality images.

Abstract: A string of computer instructions is presented to output medical image data containing voxels representative of contrast enhanced material, and arranged to operate on a first object data set comprising voxels depicting contrast enhancement, whereby it segments a sub-set of voxels in the first object data set which voxels describe contrast enhanced vessels, and uses the results of the segmentation to partition the voxels depicting contrast enhancement into a first group of voxels describing the segmented vessels and a second group of voxels describing the remaining contrast enhanced voxels, and uses the partition to output a second object data set comprising voxels depicting contrast enhancement in which the difference between the voxels of the first group and the voxels of the second group is identifiable. It is particularly advantageously applied to dynamic contrast enhanced breast imaging.