Abstract: A method for categorizing body shape is provided comprising the steps of providing a data set of body shape-defining measurements of a portion of the body of interest from a plurality of subjects' bodies, wherein the measurements define a silhouette and profile (front and side) perspectives of the portion of the body of interest; conducting a principal component (PC) analysis of the data set of measurements to calculate and generate PC scores; conducting cluster analysis using the PC scores as independent variables to produce cluster analysis results; and establishing one or more body shape categories from the cluster analysis results, thereby categorizing body shapes of the plurality of subjects. A shape prototyping system is also provided for designing a custom fit garment for an individual subject, the system being based on the method for categorizing body shape.

Abstract: A calibration device kit for generating phantom image measurements for accurately determining size of an object including a transportable casing sized to contain a synthetic calibration object. The casing containing the synthetic calibration object is adapted to be scanned to generate phantom image measurements of the at least one synthetic calibration object in relation to each of the synthetic calibration objects, a body, and the casing.

Abstract: A system and method for nodule boundary visualization superimposed on a scan image, including generating phantom image measurements of at least one synthetic calibration object in relation to a body to calibrate a scanner; acquiring a first image of a nodule on the calibrated scanner; computing and marking a boundary on the image; displaying the first image with the boundary superimposed over the first image; presenting the initial boundary to a user for modification where the user can add one or more modification points to the image to create a modified boundary that is encompassed by the one or more modification points; once the user has marked the one or more modification points on the image, computing an updated boundary that adapts to include the new points.

Abstract: A method for categorizing body shape is provided comprising the steps of providing a data set of body shape-defining measurements of a portion of the body of interest from a plurality of subjects' bodies, wherein the measurements define a silhouette and profile (front and side) perspectives of the portion of the body of interest; conducting a principal component (PC) analysis of the data set of measurements to calculate and generate PC scores; conducting cluster analysis using the PC scores as independent variables to produce cluster analysis results; and establishing one or more body shape categories from the cluster analysis results, thereby categorizing body shapes of the plurality of subjects. A shape prototyping system is also provided for designing a custom fit garment for an individual subject, the system being based on the method for categorizing body shape.

Abstract: The present invention relates to methods and systems for conducting three-dimensional image analysis and diagnosis and possible treatment relating thereto. The invention includes methods of handling signals containing information (data) relating to three-dimensional representation of objects scanned by a scanning medium. The invention also includes methods of making and analyzing volumetric measurements and changes in volumetric measurements which can be used for the purpose of diagnosis and treatment.

Abstract: The present invention relates to methods and systems for conducting three-dimensional image analysis and diagnosis and possible treatment relating thereto. The invention includes methods of handling signals containing information (data) relating to three-dimensional representation of objects scanned by a scanning medium. The invention also includes methods of making and analyzing volumetric measurements and changes in volumetric measurements which can be used for the purpose of diagnosis and treatment.

Abstract: The present invention relates to methods and systems for conducting three-dimensional image analysis and diagnosis and possible treatment relating thereto. The invention includes methods of handling signals containing information (data) relating to three-dimensional representation of objects scanned by a scanning medium. The invention also includes methods of making and analyzing volumetric measurements and changes in volumetric measurements which can be used for the purpose of diagnosis and treatment.

Abstract: The present invention is a multi-stage detection algorithm using a successive nodule candidate refinement approach. The detection algorithm involves four major steps. First, a lung region is segmented from a whole lung CT scan. This is followed by a hypothesis generation stage in which nodule candidate locations are identified from the lung region. In the third stage, nodule candidate sub-images or the lung region of the CT scan pass through a streaking artifact removal process. The nodule candidates are then successively refined using a sequence of filters of increasing complexity. A first filter uses attachment area information to remove vessels and large vessel bifurcation points from the nodule candidate list. A second filter removes small bifurcation points.

Abstract: The present invention relates to methods and systems for conducting three-dimensional image analysis and diagnosis and possible treatment relating thereto. The invention includes methods of handling signals containing information (data) relating to three-dimensional representation of objects scanned by a scanning medium. The invention also includes methods of making and analyzing volumetric measurements and changes in volumetric measurements which can be used for the purpose of diagnosis and treatment.

Abstract: A system and method for nodule boundary visualization superimposed on a scan image, including generating phantom image measurements of at least one synthetic calibration object in relation to a body to calibrate a scanner; acquiring a first image of a nodule on the calibrated scanner; computing and marking a boundary on the image; displaying the first image with the boundary superimposed over the first image; presenting the initial boundary to a user for modification where the user can add one or more modification points to the image to create a modified boundary that is encompassed by the one or more modification points; once the user has marked the one or more modification points on the image, computing an updated boundary that adapts to include the new points.

Abstract: A body part is scanned to produce a first set of imaging data. A target lesion in the imaging data is identified. The body part is rescanned at a subsequent time so as to produce a second set of imaging data. The target lesion is identified in the second set of imaging data and the size of the target lesion is measured in the first and second sets of imaging data to determine two apparent image volumes corresponding to the first and second sets of imaging data. A change in size is estimated by comparing the first and second apparent lesion sizes. A variance on the change in size is estimated so as to determine a bound on the change in size measurement.

Abstract: A visibility index for medical images. The method includes generating a visibility index from a training set of images; making a number of measurements of a set of features from an image of an abnormality that is not a member of the training set; and combining the number of measurements to generate a visibility score mapped to the visibility index.

Abstract: The present invention is a multi-stage detection algorithm using a successive nodule candidate refinement approach. The detection algorithm involves four major steps. First, a lung region is segmented from a whole lung CT scan. This is followed by a hypothesis generation stage in which nodule candidate locations are identified from the lung region. In the third stage, nodule candidate sub-images or the lung region of the CT scan pass through a streaking artifact removal process. The nodule candidates are then successively refined using a sequence of filters of increasing complexity. A first filter uses attachment area information to remove vessels and large vessel bifurcation points from the nodule candidate list. A second filter removes small bifurcation points.

Abstract: The present invention is a multi-stage detection algorithm using a successive nodule candidate refinement approach. The detection algorithm involves four major steps. First, the lung region is segmented from a whole lung CT scan. This is followed by a hypothesis generation stage in which nodule candidate locations are identified from the lung region. In the third stage, nodule candidate sub-images pass through a streaking artifact removal process. The nodule candidates are then successively refined using a sequence of filters of increasing complexity. A first filter uses attachment area information to remove vessels and large vessel bifurcation points from the nodule candidate list. A second filter removes small bifurcation points. The invention also improves the consistency of nodule segmentations. This invention uses rigid-body registration, histogram-matching, and a rule-based adjustment system to remove missegmented voxels between two segmentations of the same nodule at different times.

Abstract: Described is a method and system for conducting a clinical trial. Medical data is obtained from a patient participating in the clinical trial. Then, the medical data and at least one identifier are transmitted, via a communications network, for storage at a remote server. The at least one identifier links the medical data to a record of the patient. Access to at least portions of the medical data is provided, via the communications network, to trial participants based on predefined clinical trial procedures. The remote server tracks accessing of the medical data by the trial participants and generation by the trial participants of work product responsive to the medical data.

Abstract: The present invention is directed to diagnostic imaging of small pulmonary nodules. There are two main stages in the evaluation of pulmonary nodules from Computed Tomography (CT) scans: detection, in which the locations of possible nodules are identified, and characterization, in which a nodule is represented by measured features that may be used to evaluate the probability that the nodule is cancer. Currently, the most useful prediction feature is growth rate, which requires the comparison of size estimates from two CT scans recorded at different times. The present invention includes methods for detection and feature extraction for size characterization. The invention focuses the analysis of small pulmonary nodules that are less than 1 centimeter in size, but is also suitable for larger nodules as well.

Abstract: A method for expanding the domain of imaging software in a diagnostic work-up includes the steps of: imaging a patient's body parts for a first condition using a first imaging technique directed to a first condition; acquiring known patient risk factors indicating a second condition; compensating for differences in accuracy between a first imaging technique directed to a first condition, and a second imaging technique directed to testing for the second condition to generate a set of measures; placing a range and confidence interval around the set of measures; and evaluating for a second condition using the set of measures and known patient risk factors.

Abstract: The present invention is a multi-stage detection algorithm using a successive nodule candidate refinement approach. The detection algorithm involves four major steps. First, the lung region is segmented from a whole lung CT scan. This is followed by a hypothesis generation stage in which nodule candidate locations are identified from the lung region. In the third stage, nodule candidate sub-images pass through a streaking artifact removal process. The nodule candidates are then successively refined using a sequence of filters of increasing complexity. A first filter uses attachment area information to remove vessels and large vessel bifurcation points from the nodule candidate list. A second filter removes small bifurcation points. The invention also improves the consistency of nodule segmentations. This invention uses rigid-body registration, histogram-matching, and a rule-based adjustment system to remove missegmented voxels between two segmentations of the same nodule at different times.

Abstract: A system and method for generating an action plan for diagnosis and treatment of a patient. In particular, a historical database is complied which includes a plurality of records. Each record includes a personal profile and diagnosis data for a person. A plurality of characterizations and corresponding weighting coefficients are derived based on the records in the historical database. Pre-diagnostic patient profile data for a selected patient is obtained for the selected patient. One or more computing modules generate output data for the selected patient as a function of (i) the pre-diagnostic patient profile data, along with the physician's modifications, if any and (ii) the plurality of characterizations and corresponding weighting coefficients. The output data includes at least one of a diagnostic action plan, a confirmation action plan, a confirmation patient profile data and a therapeutic action plan.

Abstract: The present invention is a multi-stage detection algorithm using a successive nodule candidate refinement approach. The detection algorithm involves four major steps. First, the lung region is segmented from a whole lung CT scan. This is followed by a hypothesis generation stage in which nodule candidate locations are identified from the lung region. In the third stage, nodule candidate sub-images pass through a streaking artifact removal process. The nodule candidates are then successively refined using a sequence of filters of increasing complexity. A first filter uses attachment area information to remove vessels and large vessel bifurcation points from the nodule candidate list. A second filter removes small bifurcation points. The invention also improves the consistency of nodule segmentations. This invention uses rigid-body registration, histogram-matching, and a rule-based adjustment system to remove missegmented voxels between two segmentations of the same nodule at different times.