Classification of Benign and Malignant Colorectal Polyps using Pit Pattern Classification

6 Pages Posted: 23 Mar 2020

See all articles by Sushama Tanwar

Sushama Tanwar

Jaipur Engineering College and Research Centre

Pallavi M. Goel

Galgotias University

Prashant Johri

Galgotias University,

Mario Jose Divan

National University of LA Pampa

Date Written: February 21, 2020

Abstract

Colorectal cancer is the third largest cancer in the world and is second most common cause of cancer related death in the world. It has led to a large number of deaths because of not being treated on time. It originates in the form of polyps which are not cancerous. If treated on time, it can be cured otherwise it grows and converts into cancerous form and may lead to death. In this paper, we propose a deep learning technique to classify benign tumor from malignant tumor. Benign tumor is not dangerous, if removed on time as they don’t grow back after being removed whereas malignant cancer can grow back sometimes. In this paper, we propose a deep learning technique to classify benign tumor from malignant tumor. We trained our deep convolution model with a private dataset and obtained 87% accuracy. The results obtained shows that deep learning techniques can be used for timely detection of colorectal cancer so that it can be treated on time. Further, it can also be used by specialists in polyp segmentation.

Keywords: Colorectal Cancer, Deep Learning, Segmentation, Convolutional Neural Network

JEL Classification: O30

Suggested Citation

Tanwar, Sushama and Goel, Pallavi M. and Johri, Prashant and Divan, Mario Jose, Classification of Benign and Malignant Colorectal Polyps using Pit Pattern Classification (February 21, 2020). Proceedings of the 4th International Conference: Innovative Advancement in Engineering & Technology (IAET) 2020, Available at SSRN: https://ssrn.com/abstract=3558374 or http://dx.doi.org/10.2139/ssrn.3558374

Sushama Tanwar (Contact Author)

Jaipur Engineering College and Research Centre ( email )

JAIPUR
India

Pallavi M. Goel

Galgotias University ( email )

Plot No.2, Sector 17-A
Yamuna Expressway
Greater Noida, UT Uttar Pradesh 201306
India

Prashant Johri

Galgotias University, ( email )

Greater Noida, UT
India

Mario Jose Divan

National University of LA Pampa ( email )

LA Pampa
Argentina

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