Region based stellate features for classification of mammographic spiculated lesions in computer-aided detection-Reference-Cited by-同舟云学术

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Region based stellate features for classification of mammographic spiculated lesions in computer-aided detection

Published:2012-09 Issue: Volume: Page:
ISSN:
Container-title:2012 19th IEEE International Conference on Image Processing
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Author:

Kim Dae Hoe,Choi Jae Young,Ro Yong Man

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/6451323/6466779/06467486.pdf?arnumber=6467486

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Robust Method for Extracting Texture Features of Segmented Mammogram Images using M-ROI Technique;International Journal of Recent Technology and Engineering (IJRTE);2023-05-30

2. A review of mammographic region of interest classification;WIREs Data Mining and Knowledge Discovery;2020-02-18

3. Deep Learning Techniques for Breast Cancer Detection Using Medical Image Analysis;Biologically Rationalized Computing Techniques For Image Processing Applications;2017-08-18

4. Region based stellate features combined with variable selection using AdaBoost learning in mammographic computer-aided detection;Computers in Biology and Medicine;2015-08

5. Computer-aided detection (CAD) of breast masses in mammography: combined detection and ensemble classification;Physics in Medicine and Biology;2014-06-13

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