Scatter correction of cone-beam CT using a deep residual convolution neural network (DRCNN)-Reference-Cited by-同舟云学术

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Scatter correction of cone-beam CT using a deep residual convolution neural network (DRCNN)

Published:2019-07-11 Issue:14 Volume:64 Page:145003
ISSN:1361-6560
Container-title:Physics in Medicine & Biology
language:
Short-container-title:Phys. Med. Biol.

Author:

Jiang Yangkang,Yang Chunlin,Yang Pengfei,Hu Xi,Luo Chen,Xue Yi,Xu Lei,Hu Xiuhua,Zhang Luhan,Wang Jing,Sheng Ke,Niu Tianye^ORCID

Funder

Zhejiang Province 151 Talents Program

Natural Science Foundation of China

National High-tech R&D Program for Young Scientists by the Ministry of Science and Technology of China

Medical Health Science and Technology Project of Zhejiang Provincial Health Commission

Zhejiang University Education Foundation ZJU-Stanford Collaboration Fund

Zhejiang Provincial Natural Science Foundation of China

Publisher

IOP Publishing

Subject

Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://iopscience.iop.org/article/10.1088/1361-6560/ab23a6/pdf

Reference54 articles.

1. Automated planning of breast radiotherapy using cone beam CT imaging

2. Using a flat-panel detector in high resolution cone beam CT for dental imaging

3. Accelerating Monte Carlo simulations of photon transport in a voxelized geometry using a massively parallel graphics processing unit

4. Low-Dose CT With a Residual Encoder-Decoder Convolutional Neural Network

5. aLow-dose CT via convolutional neural network

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