Date of Award
Master of Science
Department of Electrical and Computer Engineering
Steven K. Rogers, PhD
The objective of this thesis is to design an automated microcalcification detection system to be used as an aid in radiologic mammogram interpretation. This research proposes the following methodology for clustered microcalcification detection. First, preprocess the digitized film mammogram to reduce digitization noise. Second, spatially filter the image with a difference of Gaussians (DoG) kernel. To detect potential microcalcifications, segment the filtered image using global and local thresholding. Next, cluster and index these detections into regions of interest (ROIs). Identify ROIs on the digitized image (or hardcopy printout) for final radiologic diagnosis.
DTIC Accession Number
Ochoa, Edward M., "Clustered Microcalcification Detection Using Optimized Difference of Gaussians" (1996). Theses and Dissertations. 5928.