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Original scientific article

AUTOMATIC SEGMENTATION OF COLON CANCER USING SAM AI

By
B. Senthil Kumar Orcid logo ,
B. Senthil Kumar

St. Joseph’s College of Engineering India

S. Karpagavalli Orcid logo ,
S. Karpagavalli

Emerson Electric Compnay India Private Limited India

K. Keerthana Orcid logo ,
K. Keerthana

Emerson Electric Compnay India Private Limited India

A. Krishnaja Orcid logo
A. Krishnaja

BGR Energy Private Limited India

Abstract

The third most prevalent form of cancer globally in both men and women is colon cancer which affects the digestive tract and occurs in the human body's greater intestine develops from certain polyps are tiisues that grow inside the colon of various sizes which at later stage can develop into a cancer cell. The tissues are taken from colon using biopsy method and cured. Under a microscope, histopathology images are categorised as a manual screening of colon the study tissue. Size of the nucleus and form of the glands are accepted standards for identifying colon cancer cells. The images obtaimed using colonscopy are converted into gray scale images where feature extraction done by conventional techniques and classified. To improve diagnosis methods for processing images and AI characteristics are also used. The automatic thresholding approach known as Otsu's Method, image thresholding, image enhancement, and edge detection techniques are used in the many processing procedures for an image. The SAM AI model is utilised to extract the malignancy characteristic of colon cancer. For the diagnostic images, metrics like resolution and peak signal to noise ratio are acquired

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Citation

This is an open access article distributed under the  Creative Commons Attribution Non-Commercial License (CC BY-NC) License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 

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