Mammography Quality Evaluation and Model Interpretation Based on CNN-based Inframammary Fold Classification
Author:
Affiliation:
1. Institute for Information Industry,Taiwan,R.O.C.
2. Tri-Service General Hospital,Taiwan,R.O.C
3. Kang-Ning General Hospital,Taiwan,R.O.C
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9979726/9979808/09980186.pdf?arnumber=9980186
Reference22 articles.
1. Improved Threshold Based and Trainable Fully Automated Segmentation for Breast Cancer Boundary and Pectoral Muscle in Mammogram Images
2. On Segmentation of Pectoral Muscle in Digital Mammograms by Means of Deep Learning
3. Utilizing Deep Learning Technology to Segment Pectoral Muscle in Mediolateral Oblique View Mammograms
4. Multi-directional Gabor filter based approach for pectoral muscle boundary detection;rahman;IEEE Trans Radiat Plasma Med Sci,2021
5. Heuristic Approach to Detect Pectoral Muscle and Nipple in Mammogram for Computer-Aided Diagnosis
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