Dual-Channel Reliable Breast Ultrasound Image Classification Based on Explainable Attribution and Uncertainty Quantification

Author:

Hu Haonan1ORCID,Lei Shuge2ORCID,Sun Desheng3ORCID,Zhang Huabin4ORCID,Yuan Kehong5ORCID,Dai Jian1ORCID,Tang Jijun2ORCID,Tong Yan2ORCID,Ye Qiongyu6ORCID

Affiliation:

1. Tsinghua Shenzhen Graduate School, China

2. University of South Carolina, United States

3. Shenzhen Hospital of Perking University, China

4. Beijing Tsinghua Changgung Hospital, Tsinghua University, China

5. Tsinghua University, China

6. Maternal and Child Health Care Hospital of Bao'an, China

Publisher

ACM

Reference32 articles.

1. C. Furbock, M. Perkonigg, T. Helbich, K. Pinker, V. Romeo, and G. Langs, “Identifying phenotypic concepts discriminating molecular breast cancer sub-types,” in International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, 2022, pp. 276–286.

2. Surpassing the Human Accuracy: Detecting Gallbladder Cancer from USG Images with Curriculum Learning

3. A. S. Panayides, A. Amini, N. D. Filipovic, A. Sharma, S. A. Tsaftaris, A. Young, D. Foran, N. Do, S. Golemati, T. Kurc ., “Ai in medical imaging informatics: current challenges and future directions,” IEEE journal of biomedical and health informatics, vol. 24, no. 7, pp. 1837– 1857, 2020.

4. Role of Breast Ultrasound for the Detection and Differentiation of Breast Lesions

5. Artificial Intelligence in Medical Imaging of the Breast

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