Scientific article
English

Deep learning-based Auto-segmentation of Organs at Risk in High-Dose Rate Brachytherapy of Cervical Cancer

Published inRadiotherapy and Oncology, vol. 159, p. 231-240
Publication date2021
Abstract

Delineation of organs at risk (OARs), such as the bladder, rectum and sigmoid, plays an important role in the delivery of optimal absorbed dose to the target owing to the steep gradient in high-dose rate brachytherapy (HDR-BT). In this work, we propose a deep convolutional neural network-based approach for fast and reproducible auto-contouring of OARs in HDR-BT.

Keywords
  • Deep learning
  • High-dose rate brachytherapy
  • Segmentation
  • Locally-advanced cervical cancer
Citation (ISO format)
MOHAMMADI, Reza et al. Deep learning-based Auto-segmentation of Organs at Risk in High-Dose Rate Brachytherapy of Cervical Cancer. In: Radiotherapy and Oncology, 2021, vol. 159, p. 231–240. doi: 10.1016/j.radonc.2021.03.030
Main files (1)
Article (Published version)
accessLevelRestricted
Secondary files (1)
Appendix
accessLevelRestricted
Identifiers
Journal ISSN0167-8140
205views
0downloads

Technical informations

Creation21/04/2021 12:13:00
First validation21/04/2021 12:13:00
Update16/03/2023 01:26:41
Status update16/03/2023 01:26:40
Last indexation31/10/2024 23:17:31
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack