Comparative analysis of automatic segmentation of esophageal cancer using 3D Res-UNet on conventional and 40-keV virtual mono-energetic CT Images: a retrospective study

Comparative analysis of automatic segmentation of esophageal cancer using 3D Res-UNet on conventional and 40-keV virtual mono-energetic CT Images: a retrospective study

Objectives To assess the performance of 3D Res-UNet for fully automated segmentation of esophageal cancer (EC) and compare the segmentation accuracy between conventional images (CI) and 40-keV virtual mono-energetic images (VMI40 kev). Methods Patients underwent spectral CT scanning and diagnosed of...

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Bibliographic Details
Main Authors: Hua Zhong, Anqi Li, Yingdong Chen, Qianwen Huang, Xingbiao Chen, Jianghe Kang, Youkuang You
Format: Article
Language:English
Published: PeerJ Inc. 2023-07-01
Series:PeerJ
Subjects:
Esophageal cancer
Dual-layer spectral-detector computed tomography
Automatic segmentation
3D Res-UNet
Virtual Monoenergetic Imaging
Online Access:https://peerj.com/articles/15707.pdf

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https://peerj.com/articles/15707.pdf

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