Abstract: A system to collect and analyze medical image data is applicable for multi-modality medical imaging systems, such as x-ray, MRI, and the like. Medical image data is collected and analyzed to determine one or more regions of interest. A selected region of interest is further analyzed to determine morphological characteristics. A feature library, which may be in the form of a data base, is used to analyze the image on a pixel-by-pixel basis to determine the degree to which the region of interest matches selected morphological characteristics, such as shape or margin. The resultant data is used to generate a map indicating a continuum over which the region of interest matches the morphological characteristics. A display receives the map data and applies it to the video image to thereby provide the user with a visualization of the degree to which the region of interest matches the morphological characteristics.

Abstract: In one embodiment, an adaptive medical image registration procedure includes a motion estimation procedure involving estimating or determining an amount of patient or tissue motion along a set of axes; an evaluation procedure involving evaluating an estimated amount of motion relative to a correction threshold; and a correction procedure involving performing a two dimensional image resampling, a three dimensional image resampling, or possibly avoiding an image resampling based upon a relationship between an estimated amount of motion and the correction threshold. Axes considered by a motion estimation procedure may include an axis of lowest image resolution, and the correction threshold may have a value given by a fraction of a lowest image resolution.

Abstract: A system to collect and analyze medical image data is applicable for multi-modality medical imaging systems, such as x-ray, MRI, and the like. Medical image data is collected and analyzed to determine one or more regions of interest. A selected region of interest is further analyzed to determine morphological characteristics. A feature library, which may be in the form of a data base, is used to analyze the image on a pixel-by-pixel basis to determine the degree to which the region of interest matches selected morphological characteristics, such as shape or margin. The resultant data is used to generate a map indicating a continuum over which the region of interest matches the morphological characteristics. A display receives the map data and applies it to the video image to thereby provide the user with a visualization of the degree to which the region of interest matches the morphological characteristics.

Abstract: A method for analyzing or processing contrast enhanced medical imaging information includes determining whether one or more candidate voxel sets within a Volume of Interest (VOI) exhibit washout curve behavior. If so, the method may identify a candidate voxel set exhibiting washout behavior as a likely malignancy. Otherwise, a method may determine whether one or more candidate voxel sets within the VOI exhibit plateau curve behavior, in which case the method may identify a candidate voxel set exhibiting plateau behavior as a likely malignancy. Otherwise, the method may identify a candidate voxel set exhibiting persistent enhancement behavior as a likely malignancy. In one embodiment, a candidate voxel set exhibiting a given type of time dependent imaging signal intensity curve or profile may be identified as a likely malignancy based upon a highest percent enhancement value.

Abstract: In one embodiment, an adaptive medical image registration procedure includes a motion estimation procedure involving estimating or determining an amount of patient or tissue motion along a set of axes; an evaluation procedure involving evaluating an estimated amount of motion relative to a correction threshold; and a correction procedure involving performing a two dimensional image resampling, a three dimensional image resampling, or possibly avoiding an image resampling based upon a relationship between an estimated amount of motion and the correction threshold. Axes considered by a motion estimation procedure may include an axis of lowest image resolution, and the correction threshold may have a value given by a fraction of a lowest image resolution.