Breast cancer (Ductal Carcinoma) detection and classification software using fuzzy pattern recognition

Breast cancer (Ductal Carcinoma) detection and classification software using fuzzy pattern recognition

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 I...

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Bibliographic Details
Main Authors: Lorenzo, Eric Meyn C., Montalban, Ivan Gregg C., Real, John Reginald G., So Kua, Donard V.
Format: text
Language:English
Published: Animo Repository 2007
Subjects:
Breast > Radiography > Automation
Image processing > Digital techniques
Computer Engineering
Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/14313
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Institution: De La Salle University
Language: English
Description
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%.

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