The characterization of mass-like breast lesions is an important step in the workup of diagnostic breast images. Categories for lesion characterization have been defined by the American College of Radiology (ACR) in the “Breast imaging reporting and data system” (Bi-rads). This standard comprises visually assessable lesion features including “shape” and “lesion margin”. In addition to these features, modality-specific features are listed, such as kinetic curve assessment in dynamic contrast enhanced MR images.
MR images of breast lesions can be visually inspected using an image viewer. Such an image viewer in many cases allows showing axial slices and multi-planar reformatted slices (MPR). Other visualization modes, such as volume rendering and surface rendering, may also be supplied.
Dynamic contrast enhanced breast MRI has been emerging as a diagnostic tool. Also, there has been a demand for computer aided diagnosis tools for this application. In order to build robust computer-aided detection (CAD) applications yielding understandable and reproducible results, a carefully selected small set of features is preferably used. In the paper “Robustness of Morphologic Features for the Characterization of Mass Lesions in Dynamic, Contrast-Enhanced Breast MR Images”, by Th. Buelow et al., ISMRM, 2008, three morphologic features are compared with respect to their robustness against variations in the mass lesion segmentations that are the input to the feature computation step. These features include “Normalized Mean Distance to Surface”, “sphericality”, and “compactness”.