Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study-Reference-Cited by-同舟云学术

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Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study

Published:2017-10-12 Issue:21 Volume:62 Page:8246-8263
ISSN:1361-6560
Container-title:Physics in Medicine & Biology
language:
Short-container-title:Phys. Med. Biol.

Author:

Zhen Xin,Chen Jiawei,Zhong Zichun,Hrycushko Brian,Zhou Linghong,Jiang Steve,Albuquerque Kevin,Gu Xuejun

Funder

National Natural Science Foundation of China

National Science Foundation

Varian Medical Systems

Publisher

IOP Publishing

Subject

Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://iopscience.iop.org/article/10.1088/1361-6560/aa8d09/pdf

Reference66 articles.

1. Locally advanced cervical cancer: what is the standard of care?

2. Bladder dose accumulation based on a biomechanical deformable image registration algorithm in volumetric modulated arc therapy for prostate cancer

3. Chest pathology detection using deep learning with non-medical training

4. Bioeffect modeling and equieffective dose concepts in radiation oncology – Terminology, quantities and units

5. Abdominal Imaging. Computational and Clinical Applications

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