Breast Cancer Detection Using Multilevel Thresholding

TL;DR

This paper introduces an image processing algorithm that combines multiple techniques to assist radiologists in early breast cancer detection from mammograms, aiming to improve diagnostic accuracy.

Contribution

The paper proposes a novel combination of image negative, thresholding, and segmentation techniques specifically for breast tumor detection in mammograms.

Findings

Effective detection of tumors in mammograms demonstrated

Algorithm verified on Mammographic Image Analysis Society dataset

Results show potential for aiding early diagnosis

Abstract

This paper presents an algorithm which aims to assist the radiologist in identifying breast cancer at its earlier stages. It combines several image processing techniques like image negative, thresholding and segmentation techniques for detection of tumor in mammograms. The algorithm is verified by using mammograms from Mammographic Image Analysis Society. The results obtained by applying these techniques are described.