Comparison of Vendor-Pretrained and Custom-Trained Deep Learning Segmentation Models for Head-and-Neck, Breast, and Prostate Cancers

Comparison of Vendor-Pretrained and Custom-Trained Deep Learning Segmentation Models for Head-and-Neck, Breast, and Prostate Cancers

Background/Objectives: We assessed the influence of local patients and clinical characteristics on the performance of commercial deep learning (DL) segmentation models for head-and-neck (HN), breast, and prostate cancers. Methods: Clinical computed tomography (CT) scans and clinically approved conto...

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Bibliographic Details
Main Authors: Xinru Chen, Yao Zhao, Hana Baroudi, Mohammad D. El Basha, Aji Daniel, Skylar S. Gay, Cenji Yu, He Wang, Jack Phan, Seungtaek L. Choi, Chelain R. Goodman, Xiaodong Zhang, Joshua S. Niedzielski, Sanjay S. Shete, Laurence E. Court, Zhongxing Liao, Fredrik Löfman, Peter A. Balter, Jinzhong Yang
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Diagnostics
Subjects:
auto-segmentation
commercial segmentation
radiotherapy
U-Net
Online Access:https://www.mdpi.com/2075-4418/14/24/2851
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