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

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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Bibliografiska uppgifter
Huvudupphovsmän: Reza Kalantar, Gigin Lin, Jessica M. Winfield, Christina Messiou, Susan Lalondrelle, Matthew D. Blackledge, Dow-Mu Koh
Materialtyp: Artikel
Språk:English
Publicerad: MDPI AG 2021-10-01
Serie:Diagnostics
Ämnen:
deep learning
pelvic cancer segmentation
radiology
radiation oncology
radiotherapy planning
Länkar:https://www.mdpi.com/2075-4418/11/11/1964

Internet

https://www.mdpi.com/2075-4418/11/11/1964

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