Application of spatial grey level dependence methods to digitized mammograms

The efficacy of using spatial grey level dependence (SGLD) methods is proposed for the evaluation of the textural content of digitized mammograms. In film-screen mammography, the physician uses his awareness of features present on the mammogram to achieve the diagnosis of (or absence of) a disease state. The image perceived by the physician represents the projection of a 3D object onto film and certain limitations are imposed by the characteristics of the imaging modality as well as by the means for creating a discrete representation of the image. Spatial grey level dependence methods have the promise to reveal significant salient information about the underlying structural elements that indicate disease and also have the potential to provide additional information with regard to the medical objective. In the paper, statistics computed from the SGLD are used to highlight features of potential medical interest in mammograms. In particular, the local energy and inertia are calculated for malignant and benign lesions. In preliminary results, it is found that these measurements have an apparent ability to provide discrimination between regions of low textural energy and randomness from regions of high textural energy and randomness. Typically, these types of regions are associated with benign and malignant image profiles, respectively. Examples are given where these techniques are applied to lesions in digitized mammograms at a 100 micron spatial resolution and 12 bit gray scale resolution