Detection of Osseous Metastasis From Bone Scintigrams Using a Combined Global and Local Patch-Based Deep Learning Model
Author:
Affiliation:
1. Ateneo Laboratory for Intelligent Visual Environments, Ateneo de Manila University, Philippines
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3685073.3685080
Reference13 articles.
1. Reza Azad Amirhossein Kazerouni Babak Azad Ehsan Khodapanah Aghdam Yury Velichko Ulas Bagci and Dorit Merhof. 2023. Laplacian-Former: Overcoming the Limitations of Vision Transformers in Local Texture Detection. arxiv:2309.00108 [cs.CV]
2. Deep Neural Network for Diagnosis of Bone Metastasis
3. Multi-level seg-unet model with global and patch-based X-ray images for knee bone tumor detection;Do Nhu-Tai;Diagnostics,2021
4. Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai Thomas Unterthiner Mostafa Dehghani Matthias Minderer Georg Heigold Sylvain Gelly Jakob Uszkoreit and Neil Houlsby. 2021. An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. arxiv:2010.11929 [cs.CV]
5. Mark Esposito, Theresa Guise, and Yibin Kang. 2018. The biology of bone metastasis. Cold Spring Harbor perspectives in medicine 8, 6 (2018), a031252.
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