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https://doi.org/10.1080/00051144.2023.2244307

Computer-aided diagnostic system for breast cancer detection based on optimized segmentation scheme and supervised algorithm

S. Balaji ; Department of Electronics and Communication Engineering, Kalasalingam Academy of Research and Education, Krishnankoil, India
T. Arunprasath ; School of Computing Science and Engineering, VIT Bhopal University, Madhya Pradesh, India
M. Pallikonda Rajasekaran ; Department of Electronics and Communication Engineering, Kalasalingam Academy of Research and Education, Krishnankoil, India
G. Vishnuvarthanan ; School of Computing Science and Engineering, VIT Bhopal University, Madhya Pradesh, India
K. Sindhuja ; Department of Electronics and Communication Engineering, Theni Kammavar Sangam College of Technology, Theni, India


Puni tekst: engleski pdf 1.844 Kb

str. 1244-1254

preuzimanja: 10

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Sažetak

Breast cancer is a serious threat to the womankind and it leads the susceptible kinds of cancer for women. The mortality rates due to breast cancer increases every single year and the World Health Organization (WHO) aims to reduce the occurrence of breast cancer by at least 2.5% per year. The occurrence of breast cancer can be minimized only when periodical screening is carried out. Mammography is one of the effective screening procedure, which can effectively locate earlier signs of breast cancer. As an aid, this work aims to present a system for the breast cancer detection and classification. This work is segregated into four phases and all these phases aim to enhance the classification performance. The efficiency of the proposed work is evaluated against the state-of-the-art approaches and the proposed contribution to the medical science. The computer-aided diagnostic system (CADS) proves 98.2% accuracy, with minimal false positive and false negative rates in a reasonable period of time.

Ključne riječi

Breast cancer detection; classification; CADS; optimization; supervised algorithm

Hrčak ID:

316002

URI

https://hrcak.srce.hr/316002

Datum izdavanja:

19.9.2023.

Posjeta: 29 *