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International Journal of Zoology and Applied Biosciences Research Article
Breast tumour detection and classification: A survey
Sangeeta Sharma, Megha Shrivastava, Ved Kumar Gupta, Neha, Neeraj Shrivastava, Yagyapal Yadav
Year : 2025 | Volume: 10 | Issue: 6 | Pages: 211-228
Received on: 11/09/2025
Revised on: 12/10/2025
Accepted on: 26/10/2026
Published on: 01/11/2025
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Sangeeta Sharma, Megha Shrivastava, Ved Kumar Gupta, Neha, Neeraj Shrivastava, Yagyapal Yadav( 2025).
Breast tumour detection and classification: A survey
. International Journal of Zoology and Applied Biosciences, 10( 6), 211-228.
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Abstract
Cancer considered as the primary wellspring of death nowadays. Cancer is by and large the unusual, uncontrolled development of cells that structure the tumour. One such cancer type is breast cancer. Early discovery, conclusion, and therapy of cancer have diminished the danger of death. Automated system for breast cancer detection will support for accurate diagnosis. The most common screening methods utilized are mammogram and Magnetic Resonance Imaging (MRI). The influence of Machine Learning (ML) in our life and our society plays an important role. To classify normal and abnormal cells for breast cancer, methods are partitioned into picture procurement, pre-handling, division, include extraction and the determination. It is possible to improve the biopsy process by which is beneficial for mammography and physical examination. This paper is centered on the survey of the cutting-edge work strategies and methods that are utilized for the identification and arrangement of breast tumour.
Keywords
Breast cancer, Deep Learning, Mammogram Images, Ultrasound Images, Thermography Images.
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© The Author(s) 2025. This article is published by International Journal of Zoology and Applied Biosciences under the terms of the Creative Commons Attribution 4.0 International License (creativecommons.org), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
