Genetic algorithm for feature selection in mammograms for breast masses classification-Reference-Cited by-同舟云学术

Genetic algorithm for feature selection in mammograms for breast masses classification

Published:2023-10-19 Issue: Volume: Page:1-12
ISSN:2168-1163
Container-title:Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization
language:en
Short-container-title:Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization

Author:

G Vaira Suganthi ¹^ORCID,J Sutha ²,M Parvathy ¹,Muthamil Selvi N³

Affiliation:

1. Department of Computer Science and Design, Sethu Institute of Technology, Kariapatti, India

2. Department of Computer Science and Engineering, AAA College of Engineering and Technology, Sivakasi, India

3. Department of Artificial Intelligence and Data Science, KLN College of Engineering, Sivagangai, India

Funder

No funding

Publisher

Informa UK Limited

Subject

Computer Science Applications,Radiology, Nuclear Medicine and imaging,Biomedical Engineering,Computational Mechanics

Link

https://www.tandfonline.com/doi/pdf/10.1080/21681163.2023.2266031

Reference41 articles.

1. Analysis of tissue abnormality and breast density in mammographic images using a uniform local directional pattern

2. Comparing supervised and semi-supervised Machine Learning Models on Diagnosing Breast Cancer

3. Al-Masni MA. 2017. Detection and classification of the breast abnormalities in digital mammograms via regional convolutional neural network. Proceedings of 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

4. Amara N, Shoaib M, Gattoufi S. 2018. Detection and classification of the breast abnormalities in digital mammograms via linear support vector machine. IEEE 4th Middle East Conference on Biomedical Engineering (MECBME); 28-30 March 2018; Tunis, Tunisia. IEEE. p. 141–146. doi: 10.1109/MECBME.2018.8402422.

5. A novel machine learning approach for breast cancer diagnosis