State-of-art Techniques for Classification of Breast Cancer: A Review

Title

State-of-art Techniques for Classification of Breast Cancer: A Review

Creator

Rajput D.; Bejoy B.J.

Description

Cancer is an unexpected and unclear disease that puts many people at risk. Breast cancer has surpassed prostate cancer as the most common cancer in women, as well as the main cause of cancer-related mortality in women. Breast cancer rates have been rising in India for several years, with 100,000 new cases recorded each year. In India, there are up to one million breast cancer patients at any given moment. The survival rate of breast cancer has increased in recent years as a result of advances in technology, effective treatment, and medical care delivery. It extends the lives of the sufferers and improves their quality of life. Breast cancer can be detected using a variety of imaging methods. Radiologists can utilize a computer-aided diagnostic technique to discover and diagnose irregularities earlier and more quickly. Many Computer-Aided Diagnosis methods have been developed to identify breast cancer in its early stages using mammography images. The computer aided diagnostics systems mostly focus on identifying and detecting breast nodules. Staging breast cancer at its detection needs to be focused on, as the treatment is based on the stage of cancer. As a result, this study focuses on producing evaluations on computer aided diagnostics approaches for segmenting nodules and identifying different stages of breast cancer, thereby assisting radiologists in assessing the illness. 2022 IEEE.

Source

Proceedings of 5th International Conference on Contemporary Computing and Informatics, IC3I 2022, pp. 433-437.

Date

2022-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Breast Cancer; Classification; Deep Learning (DL); Machine Learning (ML); Mammogram; Neural Network (NN)

Coverage

Rajput D., CHRIST (Deemed to Be University), Department of CSE, Bengaluru, India; Bejoy B.J., CHRIST (Deemed to Be University), Department of CSE, Bengaluru, India

Rights

Restricted Access

Relation

ISBN: 979-835039826-7

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/IC3I56241.2022.10073435

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152000610&doi=10.1109%2fIC3I56241.2022.10073435&partnerID=40&md5=aa958d86e900d9e5f4ec1922018f51b4