Comparing multi-image and image augmentation strategies for deep learning-based prostate segmentation-Reference-Cited by-同舟云学术

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Comparing multi-image and image augmentation strategies for deep learning-based prostate segmentation

Published:2024-01 Issue: Volume:29 Page:100551
ISSN:2405-6316
Container-title:Physics and Imaging in Radiation Oncology
language:en
Short-container-title:Physics and Imaging in Radiation Oncology

Author:

Fransson Samuel

Publisher

Elsevier BV

Reference28 articles.

1. Clinical evaluation of atlas and deep learning based automatic contouring for lung cancer;Lustberg;Radiother Oncol,2018

2. Benefits of deep learning for delineation of organs at risk in head and neck cancer;van der Veen;Radiother Oncol,2019

3. Comparative evaluation of autocontouring in clinical practice: A practical method using the Turing test;Gooding;Med Phys,2018

4. A Deep Learning-Based Automated CT Segmentation of Prostate Cancer Anatomy for Radiation Therapy Planning-A Retrospective Multicenter Study;Kiljunen;Diagnostics,2020

5. Evaluating the Effectiveness of Deep Learning Contouring across Multiple Radiotherapy Centres;Walker;Phys Imaging Radiat Oncol,2022

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