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Automatic Colorectal Polyp Detection in Colonoscopy Video Frames

Geetha k¹, Rajan c

¹Department of Information Technology, Excel Engineering College, India.

Asian Pacific Journal of Cancer Prevention : APJCP

|December 30, 2016

Summary

This study introduces a computer-aided detection (CAD) system using local binary patterns (LBPs) for identifying colorectal polyps during colonoscopy. The proposed method demonstrates superior performance compared to existing techniques in detecting these precancerous lesions.

Keywords:

Colon cancer colonoscopy Local Binary Pattern (LBP)J48 Fuzzy Discrete Cosine Transform (DCT

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Published on: October 16, 2013

Area of Science:

Gastroenterology
Medical Imaging
Computer Science

Background:

Colonoscopy is the primary method for detecting colon cancer and precancerous lesions.
Computer-aided detection (CAD) systems utilize complex pattern recognition for enhanced diagnostic accuracy.
Local binary patterns (LBPs) are effective texture descriptors, invariant to illumination changes.

Purpose of the Study:

To develop and evaluate a novel CAD system for colorectal polyp detection using colonoscopy video frames.
To assess the efficacy of LBPs, color, and discrete cosine transform (DCT) features in polyp classification.
To compare the proposed method's performance against existing colorectal polyp detection techniques.

Main Methods:

Utilized colonoscopy video frames for colorectal polyp detection.
Employed local binary patterns (LBPs) as texture primitives for feature extraction.
Implemented J48 and Fuzzy classification algorithms for polyp identification.
Integrated color and discrete cosine transform (DCT) features alongside LBPs.

Main Results:

The proposed CAD system achieved superior performance in colorectal polyp detection.
Feature analysis confirmed the effectiveness of LBP, color, and DCT in enhancing detection accuracy.
The method outperformed other current approaches for identifying colorectal polyps.

Conclusions:

The developed CAD system, incorporating LBP, color, and DCT features, offers a highly effective approach for colorectal polyp detection.
This advanced technique holds significant potential for improving early diagnosis and management of colorectal cancer.
The study highlights the superiority of the proposed method in enhancing colonoscopy's diagnostic capabilities.