Clustered Microcalcification Detection Using Optimized Difference of Gaussians

Author

Edward M. Ochoa

Date of Award

12-1996

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Electrical and Computer Engineering

First Advisor

Steven K. Rogers, PhD

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.

AFIT Designator

AFIT-GE-ENG-96D-13

DTIC Accession Number

ADA325042

Recommended Citation

Ochoa, Edward M., "Clustered Microcalcification Detection Using Optimized Difference of Gaussians" (1996). Theses and Dissertations. 5928.
https://scholar.afit.edu/etd/5928