Fully convolutional network for automated detection and diagnosis of mammographic masses
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-14757-8.pdf
Reference44 articles.
1. Agarwal R, Díaz O, Yap M H, Lladó X, Martí R (2020) Deep learning for mass detection in full field digital mammograms. Comput Biol Med 121:103774. https://doi.org/10.1016/j.compbiomed.2020.103774
2. Agarwal R, Diaz O, Lladó X, Yap M H, Martí R (2019) Automatic mass detection in mammograms using deep convolutional neural networks. J Med Imag 6(3):1–9. https://doi.org/10.1117/1.JMI.6.3.031409
3. Akselrod-Ballin A, Karlinsky L, Alpert S, Hasoul S, Ben-Ari R, Barkan E (2016) A region based convolutional network for tumor detection and classification in breast mammography. In: Carneiro G, Mateus D, Peter L, Bradley A, Tavares JMR S, Belagiannis V, Papa JP, Nascimento JC, Loog M, Lu Z, Cardoso JS, Cornebise J (eds) Deep learning and data labeling for medical applications. Springer International Publishing, Cham, pp 197–205
4. Al-antari M A, Al-masni M, Choi M-T, Han S-M, Kim T-S (2018) A fully integrated computer-aided diagnosis system for digital x-ray mammograms via deep learning detection, segmentation, and classification. Int J Med Informatics, 117. https://doi.org/10.1016/j.ijmedinf.2018.06.003
5. Al-masni M A, Al-antari M A, Park J-M, Gi G, Kim T-Y, Rivera P, Valarezo E, Choi M-T, Han S-M, Kim T-S (2018) Simultaneous detection and classification of breast masses in digital mammograms via a deep learning yolo-based cad system. Comput Methods Programs Biomed 157:85–94. https://doi.org/10.1016/j.cmpb.2018.01.017
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