Breast cancer (Ductal Carcinoma) detection and classification software using fuzzy pattern recognition
Date of Publication
2007
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Computer Engineering
Subject Categories
Computer Engineering
College
Gokongwei College of Engineering
Department/Unit
Electronics and Communications Engineering
Thesis Adviser
Enrique M. Manzano
Defense Panel Member
Martin Christian G. Leonor
Jingel A. Tio
Abstract/Summary
The research deals on the detection and classification of Breast Carcinoma particularly Ductal Carcinoma. The study takes on the characteristics and definitions of Ductal Carcinoma by having a digital image from stained breast tissue samples, as seen in the microscope, analyzed and evaluated using Image Processing (first module) and Fuzzy Pattern Recognition (second module). The first module analyzes the Terminal Duct Lobular Unit (TDLU) by implementing a number of processing techniques such as Nuclei Extraction, Filtering and Feature Extraction to name a few. The second module uses Fuzzy Membership Functions to evaluate the degree and level at which the image is an Invasive Carcinoma (malignant) or Noninvasive (benign) and if invasive, would it be an Invasive Ductal Carcinoma NST (no specific type) or of a different type. The overall accuracy of the study is 95%.
Abstract Format
html
Language
English
Format
Accession Number
TU14007
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
135, [3] leaves : col. ill.: 28 cm
Keywords
Breast--Radiography--Automation; Image processing--Digital techniques
Recommended Citation
Lorenzo, E. C., Montalban, I. C., Real, J. G., & So Kua, D. V. (2007). Breast cancer (Ductal Carcinoma) detection and classification software using fuzzy pattern recognition. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/14313