Deep learning-enabled accurate normalization of reconstruction kernel effects on emphysema quantification in low-dose CT-Reference-Cited by-同舟云学术

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Deep learning-enabled accurate normalization of reconstruction kernel effects on emphysema quantification in low-dose CT

Published:2019-07-04 Issue:13 Volume:64 Page:135010
ISSN:1361-6560
Container-title:Physics in Medicine & Biology
language:
Short-container-title:Phys. Med. Biol.

Author:

Jin Hyeongmin,Heo Changyong,Kim Jong Hyo

Funder

Ministry of Science and ICT

Ministry of Trade, industry & Energ

Publisher

IOP Publishing

Subject

Radiology Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://iopscience.iop.org/article/10.1088/1361-6560/ab28a1/pdf

Reference40 articles.

1. Equating quantitative emphysema measurements on different CT image reconstructions

2. Emphysema: Effect of Reconstruction Algorithm on CT Imaging Measures

3. Robust, Standardized Quantification of Pulmonary Emphysema in Low Dose CT Exams

4. Standardizing CT lung density measure across scanner manufacturers

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

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