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 method for error correction for segmented three dimensional image data. The method includes receiving segmented three dimensional image data, the segmented three dimensional image data being divided into a plurality of slices; correcting at least one contour of the segmented three dimensional image data on at least one slice according to a command from a user to form a corrected contour; and automatically interpolating a correction represented by the corrected contour to a plurality of slices of the segmented three dimensional image data.

Abstract: A system and method for voice to text reporting for medical image software. The system and method may optionally include a separate voice to text engine, for converting the voice report to text, and also some type of medical image software, for providing medical image processing capabilities. According to at least some embodiments, both capabilities are provided remotely to the user's computer, and may optionally be provided through a “zero footprint” on the user's computer.

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 for error correction for segmented three dimensional image data. The method includes receiving segmented three dimensional image data, the segmented three dimensional image data being divided into a plurality of slices; correcting at least one contour of the segmented three dimensional image data on at least one slice according to a command from a user to form a corrected contour; and automatically interpolating a correction represented by the corrected contour to a plurality of slices of the segmented three dimensional image data.