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

Print

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

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