Abstract: A method of segmenting a target organ of the body in medical images, the method comprising: providing a probabilistic atlas with probabilities for a presence of the target organ at different locations relative to a bounding region of the target organ; providing one or more medical test images; for each test image, identifying, at least provisionally, a location of a bounding region for the target organ in the test image; and for each test image, using the probabilities from the probabilistic atlas to segment the target organ in the test image, with the segmenting performed by a data processor.

Abstract: A method of processing a medical image comprising an organ, the method comprising: obtaining a medical image; automatically estimating one or more organ intensity characteristics in the image, from contents of a region of the image that appears to correspond, at least in part, to at least a portion of the organ; providing a plurality of sets of organ intensity characteristics, each set a different example of possible intensity characteristics of the organ; choosing one of the plurality of sets, that has organ intensity characteristics that provide a better match than one or more other sets to the estimated organ intensity characteristics of the image; setting values of one or more image processing parameters based on the organ intensity characteristics of the chosen set; and automatically processing the image using said values of image processing parameters.

Abstract: A method for automated segmentation of a blood vessel of a head and neck of a subject in a medical image, the method comprising: identifying the location of anatomical landmarks in the medical image; identifying regions of interest in the medical image based on the landmarks; segmenting segments of blood vessels in the medical image; classifying at least one of the segments as defining the blood vessel based on its position relative to the landmarks within the regions of interest to create a classified blood vessel; identifying a starting seed for the blood vessel from the classified blood vessel; identifying an ending seed for the blood vessel from the classified blood vessel; segmenting the blood vessel between the starting seed and the ending seed; and defining a path between the starting seed and the ending seed.

Abstract: A system and method for automatic detection of an object feature, such as a lesion, across a plurality of sets of image data, taken from the same subject, which may optionally be a human patient but which may also optionally be any type of animal or a non-biological subject.

Abstract: A method and system which displays a single image after a plurality of windows have been applied to image data according to one or more organ masks. The method is accomplished by collecting a radiological scan from an imaging device to form image data; obtaining an anatomically significant mask for said image data; determining a portion of said image data as background; applying a plurality of windows to said image data determined according to said anatomically significant mask and according to said background to determine display values of said image data; and generating a generated display image from said display values.

Abstract: A system and method for automatic detection of an object feature, such as a lesion, across a plurality of sets of image data, taken from the same subject, which may optionally be a human patient but which may also optionally be any type of animal or a non-biological subject.