Automatic Segmentation of Pelvic Cancers Using Deep Learning: State-of-the-Art Approaches and Challenges

The recent rise of deep learning (DL) and its promising capabilities in capturing non-explicit detail from large datasets have attracted substantial research attention in the field of medical image processing. DL provides grounds for technological development of computer-aided diagnosis and segmenta...

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Bibliographic Details
Main Authors:	Reza Kalantar, Gigin Lin, Jessica M. Winfield, Christina Messiou, Susan Lalondrelle, Matthew D. Blackledge, Dow-Mu Koh
Format:	article
Language:	EN
Published:	MDPI AG 2021
Subjects:	deep learning pelvic cancer segmentation radiology radiation oncology radiotherapy planning Medicine (General) R5-920
Online Access:	https://doaj.org/article/7aff8e47b4f149db9b8f67a8f0fb6c4f
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Automatic Segmentation of Pelvic Cancers Using Deep Learning: State-of-the-Art Approaches and Challenges

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