Abstract: A method for automatically detecting pulmonary embolism (PE) candidates within medical image data using an image processing device includes administering radiocontrast into a patient. A sequence of computed tomography (CT) images is acquired. A level of radiocontrast at a pulmonary artery trunk of the patient is determined. One or more PE candidates are detected within a pulmonary artery tree of the patient based on the determined level of radiocontrast at the pulmonary artery trunk. The one or more detected PE candidates are displayed.

Abstract: A method of detecting blood vessel shadows in an anterior posterior x-ray radiograph comprising the steps of: generating candidate sub areas of the radiograph showing changes in contrast above a threshold level; supressing rib shadow edges; eliminating lung tissue shadow edges, and categorizing and eliminating nodule shadows.

Abstract: Detected lung nodules are presented in a chest radiographic sub-image. A curve is matched to pixels in the sub-image and confidence values for individual pixels is determined. A confidence image is generated consisting of the confidence values at the position of the respective pixel. Separated regions of pixels within the confidence image are identified which have a confidence value greater than a threshold confidence value. A filtered confidence image is generated consisting of the separated regions of the confidence image which are larger than a threshold area. A histogram of values characteristic for the matching of the curve is determined, wherein the filtered confidence image is used as a mask, such that only values are considered for the histogram which correspond to the separated regions of the filtered confidence image. A statistical measure of the histogram is determined and the lung nodules are verified based on the statistical measure.

Abstract: A method of detecting lung nodules in an anterior posterior x-ray radiograph comprising the steps of: generating candidate regions in image showing changes in contrast above a threshold level, and eliminating false positives by eliminating edges assignable to organs by: identifying edges; categorizing and eliminating rib edges; categorizing and eliminating lung tissue edges, and categorizing and eliminating blood vessels.

Abstract: A method for lesion detection includes acquiring pre-therapy medical image data from a first modality. Post-therapy medical image data is acquired from a second modality. A transformation matrix for transforming from an image space of the first modality to an image space of the second modality is calculated. A volume of interest is defined from the medical image data of the first modality. The volume of interest includes one or more lesions. The volume of interest is automatically copied to the medical image data of the second modality using the calculated transformation matrix. Treatment is directed to the lesion using the medical image data of the second modality including the copied volume of interest data.

Abstract: A system and method for generating test frames in specification-based testing by using a path-coverage criterion is provided. The method includes receiving a test design as an input, and constructing a context-free grammar graph, based on the test design. The method further includes analyzing the context-free grammar graph to generate a first set of paths, and emitting a set of test frames as an output, based on the first set of paths.