Accession Number : ADA325042
Title : Clustered Microcalcification Detection Using Optimized Difference of Gaussians.
Descriptive Note : Master's thesis,
Corporate Author : AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH
Personal Author(s) : Ochoa, Edward M.
PDF Url : ADA325042
Report Date : DEC 1996
Pagination or Media Count : 99
Abstract : 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.
Descriptors : *DETECTION, *CALCIFICATION, *BREAST CANCER, ALGORITHMS, NEURAL NETS, RESOLUTION, THESES, DIAGNOSIS(MEDICINE), CLUSTERING, IMAGES, PATTERN RECOGNITION, FILTERS, NOISE, ANALOG TO DIGITAL CONVERTERS, GENETICS, RADIOLOGY, MAMMOGRAPHY.
Subject Categories : Computer Hardware
Medicine and Medical Research
Distribution Statement : APPROVED FOR PUBLIC RELEASE