Artificial Intelligence in Breast Imaging
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-94918-1_20
Reference95 articles.
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3. Arefan D, Mohamed AA, Berg WA, Zuley ML, Sumkin JH, Wu S (2020) Deep learning modeling using normal mammograms for predicting breast cancer risk. Med Phys 47(1):110–118
4. Bahl M (2020) Artificial intelligence: a primer for breast imaging radiologists. J Breast Imaging 2(4):304–314
5. Barinov L, Jairaj A, Becker M, Seymour S, Lee E, Schram A et al (2019) Impact of data presentation on physician performance utilizing artificial intelligence-based computer-aided diagnosis and decision support systems. J Digit Imaging 32(3):408–416
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1. DisAsymNet: Disentanglement of Asymmetrical Abnormality on Bilateral Mammograms Using Self-adversarial Learning;Lecture Notes in Computer Science;2023
2. Deep Learning on Ultrasound Imaging for Breast Cancer Diagnosis and Treatment: Current Applications and Future Perspectives;ADVANCED ULTRASOUND IN DIAGNOSIS AND THERAPY;2023
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