Abstract: Methods and systems for quantification of a selected attribute of an image volume are provided. The system is configured to receive an image dataset for a volume of interest, process the dataset for a selected attribute based at least on one of shape and texture to obtain a plurality of responses, and compute an index of an aggregate of a plurality of obtained responses.

Abstract: Certain embodiments of the present invention provide a system and method for identifying stool particles in virtual dissection data for a colon. A shape classification may be determined for a segmented colon by three-dimensional filtering of a prone data set and a supine data set. The shape classification may be mapped onto a prone virtual dissection image and a supine virtual dissection image. The prone data set and the supine data set may be registered using one-dimensional registration to determine a registration. Shapes may be localized based on the shape classification and the registration for the prone virtual dissection and the supine virtual dissection. A distance metric may be applied to the localized shapes to identify stool particles. The identified stool particles may be suppressed. A prone virtual dissected image and a supine virtual dissected image may be displayed having the stool particles suppressed.

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing patient image and non-image deviation scores derived through respective comparisons of patient image and non-image data to standardized image and non-image data. The method may also include processing the image and non-image deviation scores to generate a visual output indicative of differences between the patient image and non-image data, and the standardized image and non-image data, respectively. Further, the method may include displaying the visual output. Additional methods, systems, and manufactures are also disclosed.

Abstract: A system and method for analyzing and visualizing spectral CT data includes access of a set of image data acquired from a patient comprising spectral CT data, identification of a plurality of target regions of interest (TROIs) and a reference region of interest (RROI) from the set of image data, extraction of a plurality of target spectral Hounsfield unit (HU) curves from image data representing the plurality of TROIs, extraction of a reference spectral HU curve from image data representing the RROI, normalization of the plurality of target spectral HU curves with respect to the reference spectral HU curve, and display of the plurality of normalized target spectral HU curves.

Abstract: A system and method for displaying a set of data with a virtually dissected anatomical structure. In an embodiment, the anatomical structure is a colon and various attributes of the colonic lumen are assigned a color. In an embodiment, a virtual dissection of the colon is created by mapping a three-dimensional data set to a two dimensional data set. A plurality of display index values are computed which correspond to the three-dimensional data set. Various colors are assigned to specific display index values. The three-dimensional display index values are mapped to a two-dimensional set of display index values. As directed by a user, various color cues may be displayed with the virtually dissected lumen to provide color highlights to various aspects of the colon, such as highlighting shape, fluid, or fecal presence.

Abstract: A method is provided for synchronizing corresponding landmarks among a plurality of images of an elastic object. The method includes identifying a plurality of landmarks in a first image of the object and a second image of the object, determining a correspondence between the landmarks in the first image and the landmarks in the second image, determining a distance transformation between a pair of adjacent landmarks in the first image and the corresponding pair of adjacent landmarks in the second image, and when displaying the first and second images, using the distance transformation to smoothly navigate between the adjacent landmarks such that corresponding landmarks of the first and second images are arrived at about simultaneously during navigation.

Abstract: A method for enhancing images of an object includes registering a fixed image with cine images of the same object. Next, the fixed image and the cine images are transformed into frequency space representations thereof. A central portion of the frequency space cine images are merged with a peripheral portion of frequency space fixed image using a defined normalized response curve or a predefined normalized response curve (or both) to form a merged image. Finally, the method includes inversely transforming the merged image into enhanced cine images of the object.

Abstract: A system and method for analyzing and visualizing a local feature of interest includes access of a clinical image dataset comprising clinical image data acquired from a patient, identification of a region of interest (ROI) from the clinical image dataset, and extraction of at least one local feature corresponding to the ROI. The system and method also include definition of a local feature dataset comprising data representing at least one local feature, access of a pre-computed reference dataset comprising image data representing an expected value of the at least one identified derived characteristic of interest, and comparison of the characteristic dataset to the pre-computed reference dataset. Further, the system and method include calculation of at least one deviation metric from the comparison and output of a visualization of the at least one deviation metric.

Abstract: A method for processing computed tomography (CT) datasets comprises identifying regions of interest (ROIs) within a CT dataset is provided. The ROIs are ranked based on a comparison to at least one predetermined parameter. The ranking determines a level of importance for the ROIs with respect to each other. A list of the ROIs is provided on a display, the list indicating the ROIs based on an associated level of importance. The ROIs are selectable with a user interface.

Abstract: Systems, methods and apparatus are provided through which in some implementations changes in an aneurysm in a patient over time are identified by determining temporal differences between segmented aneurysms in a plurality of longitudinal exams and visually presenting the temporal differences.

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing individual patient deviation maps indicative of a structural difference and a functional difference, respectively, of at least one anatomical region of a patient with respect to standardized reference image data. The method may also include generating a composite patient deviation map indicative of both the structural difference and the functional difference based on at least the individual patient deviation maps, and outputting the composite patient deviation map. Additional methods, systems, and manufactures are also disclosed.

Abstract: Methods and apparatus for reconstructing a multiple resolution images of an object are provided. The method includes reconstructing a first three-dimensional image at a first resolution, determining at least one volume of interest in the generated image, and reconstructing a second three-dimensional image of the determined at least one volume of interest at a second resolution, the second resolution being higher than the first resolution such that a quantification of image structures is facilitated.

Abstract: Methods and apparatus for coding a visual representation of one or more plaque regions in a vessel are provided. The method includes segmenting the visual representation of the vessel to identify structures associated with the vessel, classifying at least one region in the vessel as a plaque region, displaying the at least one plaque region using a visual highlight selectively associated with the classification for the at least one plaque region, and shading the visual highlight based on a probability that the classification is correct.

Abstract: A method includes generating a first response including a plurality of potential first objects of interest of a first shape from data regarding a region of interest (ROI), generating a second response including a plurality of second objects of interest for a second shape different than the first shape from the data regarding the ROI, and performing a morphological closing on the second response to produce a second cleaned response including a plurality of completed second objects. The method also includes decreasing the number of potential objects of interest in the first response by deleting any potential first objects that overlap any completed second objects to obtain a cleaned first response, and generating an image using at least one of the first cleaned response and the second cleaned response.

Abstract: A system comprising a memory device having a plurality of routines stored therein, a processor configured to execute the plurality of routines stored in the memory device, the plurality of routines comprising: a routine configured to effect, when executed, accessing of patient deviation scores indicative of differences between patient data and reference data representative of a population segment, wherein the patient deviation scores are derived from longitudinal data of the patient data such that the patient deviation scores include a plurality of sets of patient deviation scores, each set indicative of differences between patient data collected at a respective point in time and the reference data; a routine configured to effect, when executed, identifying a trend in the patient deviation scores for at least one clinical parameter; a routine configured to effect, when executed, generating of a report including a visual indication of the trend; and a routine configured to effect, when executed, outputting of

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing patient deviation data of a structural difference between a patient anatomical feature and a standardized anatomical feature. The method may also include comparing the patient deviation data to reference deviation data sets representative of multiple disease types. Each reference deviation data set may be representative of an expected deviation from the standardized anatomical feature for a particular disease type. The method may further include automatically identifying one or more potential patient disease types based at least in part on the comparison. Additional methods, systems, and manufactures are also disclosed.

Abstract: A method for suppressing tagged material in prepless colonoscopy includes identifying and segmenting multiple density classes, intensity classes, or both in a volumetric medical image of a patient including a volume of the patient's colon and classifying the volume of the patient's colon into a plurality of types based upon the identified and segmented density classes, intensity classes, or both. The method further includes subtracting, suppressing, or leaving the tagged material in the image in accordance with the type classifications to produce a resulting image and visualizing the resulting image.

Abstract: A technique for selecting portions of a multi-resolution medical image data set to be stored and the portions of the multi-resolution medical image data set to be discarded in order to reduce the overall amount of image data that is stored for each image data set. The selection is based on the clinical purpose for obtaining the medical image data. The clinical purpose for obtaining the medical image is used to define regions of interest in the medical image. At each resolution level of the multi-resolution medical image data set, the regions of interest are stored at the full resolution, while the remaining portions of the medical image are stored at a lesser resolution. A three-dimensional bit mask of the regions of interest is produced from a segmentation of the regions of interest. The segmentation list and the multi-resolution medical image data set are decomposed into multiple resolution levels. Each resolution level has a low frequency component and several high frequency components.

Abstract: A method for managing data transmission between computing devices is disclosed. In one embodiment, the method includes monitoring a plurality of parameters of a computer network that includes a server and a client. The plurality of parameters may include a client resource parameter, a server resource parameter, and a network operating parameter. The disclosed method may also include automatically determining a desired compression level at which to send data to the client based at least in part on the client resource parameter, the server resource parameter, and the network operating parameter. Further, in one embodiment the method may include communicating the data from the server to the client at the desired compression level in response to a client request for the data. Various other methods, systems, and manufactures are also disclosed.

Abstract: A method for generating a score for soft plaque in coronary arteries includes using the computer to estimate the soft plaque content within at least one object depicted in a medical image, using the computer to determine a plaque score dependent upon the estimated soft plaque content of the at least one object, and using the computer to report the plaque score.