Issue |
MATEC Web Conf.
Volume 392, 2024
International Conference on Multidisciplinary Research and Sustainable Development (ICMED 2024)
|
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Article Number | 01136 | |
Number of page(s) | 7 | |
DOI | https://doi.org/10.1051/matecconf/202439201136 | |
Published online | 18 March 2024 |
Effective texture features in mammogram images via multi-roi segmentation
1 Department of Computer Science and Engineering (CS), Institute of Aeronautical Engineering, Hyderabad, Telangana, India.
2 KG Reddy College of Engineering and Technology, Hyderabad, Telangana, India.
* Corresponding author: krprgm@gmail.com
Digital mammography increasingly necessitates image segmentation for the purpose of dividing mammograms into individual slices. For the purpose of removing suspicious masses or tumours from mammograms, this process is carried out using a region of interest (ROI). More training photos are needed for mammography image classification, and these circumstances, ROI requires more processing time. The temporal complexity difficulties with the suggested multi-ROI method are the subject of this article. To show how effective the suggested multi-ROI is compared to the current segmentation approach, experiments are conducted on benchmarked datasets.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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