Faster R-CNN based on Optimized SqueezeNet for Liver Lesion Detection from DeepLesion Dataset-Reference-Cited by-同舟云学术

Faster R-CNN based on Optimized SqueezeNet for Liver Lesion Detection from DeepLesion Dataset

Published:2021-06-25 Issue: Volume: Page:
ISSN:
Container-title:2021 the 5th International Conference on Graphics and Signal Processing
language:
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Author:

Alkhaleefah Mohammad¹,Tan Tan-Hsu¹,Achhannagari Vishnu Priya¹,Ma Shang-Chih¹,Tsai Min-Jui¹,Chang Yang-Lang¹

Affiliation:

1. National Taipei University of Technology, Taiwan

Funder

Ministry of Science and Technology, Taiwan,

National Taipei University of Technology and Cheng Hsin General Hospital,

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3474906.3474914

Reference30 articles.

1. Lei Bi Jinman Kim Ashnil Kumar and Dagan Feng. 2017. Automatic liver lesion detection using cascaded deep residual networks. arXiv preprint arXiv:1704.02703(2017). Lei Bi Jinman Kim Ashnil Kumar and Dagan Feng. 2017. Automatic liver lesion detection using cascaded deep residual networks. arXiv preprint arXiv:1704.02703(2017).

2. Paramita Dasgupta Chloe Henshaw Danny R Youlden Paul J Clark Joanne F Aitken and Peter D Baade. 2020. Global trends in incidence rates of primary adult liver cancers: A systematic review and meta-analysis. Frontiers in oncology 10(2020) 171. Paramita Dasgupta Chloe Henshaw Danny R Youlden Paul J Clark Joanne F Aitken and Peter D Baade. 2020. Global trends in incidence rates of primary adult liver cancers: A systematic review and meta-analysis. Frontiers in oncology 10(2020) 171.

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