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Automatic Segmentation of Head and Neck Tumor: How Powerful Transformers Are?. (arXiv:2201.06251v2 [eess.IV] UPDATED)
Web: http://arxiv.org/abs/2201.06251
May 13, 2022, 1:11 a.m. | Ikboljon Sobirov, Otabek Nazarov, Hussain Alasmawi, Mohammad Yaqub
cs.LG updates on arXiv.org arxiv.org
Cancer is one of the leading causes of death worldwide, and head and neck
(H&N) cancer is amongst the most prevalent types. Positron emission tomography
and computed tomography are used to detect, segment and quantify the tumor
region. Clinically, tumor segmentation is extensively time-consuming and prone
to error. Machine learning, and deep learning in particular, can assist to
automate this process, yielding results as accurate as the results of a
clinician. In this paper, we investigate a vision transformer-based method …
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