Empowering Vision Transformer by Network Hyper-Parameter Selection for Whole Pelvis Prostate Planning Target Volume Auto-Segmentation

Empowering Vision Transformer by Network Hyper-Parameter Selection for Whole Pelvis Prostate Planning Target Volume Auto-Segmentation

U-Net, based on a deep convolutional network (CNN), has been clinically used to auto-segment normal organs, while still being limited to the planning target volume (PTV) segmentation. This work aims to address the problems in two aspects: 1) apply one of the newest network architectures such as visi...

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Bibliographic Details
Main Authors: Hyeonjeong Cho, Jae Sung Lee, Jin Sung Kim, Woong Sub Koom, Hojin Kim
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Cancers
Subjects:
transformer
hyper-parameter selection
planning target volume
auto-segmentation
prostate cancer
VT U-Net v.2
Online Access:https://www.mdpi.com/2072-6694/15/23/5507

Internet

https://www.mdpi.com/2072-6694/15/23/5507

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