Classifying functional nuclear images with convolutional neural networks: a survey-Reference-Cited by-同舟云学术

Classifying functional nuclear images with convolutional neural networks: a survey

Published:2020-10-21 Issue:14 Volume:14 Page:3300-3313
ISSN:1751-9659
Container-title:IET Image Processing
language:en
Short-container-title:IET image process

Author:

Lin Qiang¹²^ORCID,Man Zhengxing¹²,Cao Yongchun¹²,Deng Tao¹²,Han Chengcheng¹²,Cao Chuangui¹²,Zhang Linjun²³,Zeng Sitao²³,Gao Ruiting²³,Wang Weilan³,Ji Jinshui¹²,Huang Xiaodi⁴

Affiliation:

1. School of Mathematics and Computer Science, Northwest Minzu UniversityNo. 1 Xibei Xincun RoadLanzhouPeople's Republic of China

2. Key Laboratory of Streaming Data Computing Technologies and Application, Northwest Minzu UniversityNo. 1 Xibei Xincun RoadLanzhouPeople's Republic of China

3. Key Laboratory of China's Ethnic Languages and Information Technology of Ministry of Education, Northwest Minzu UniversityNo. 1 Xibei Xincun RoadLanzhouPeople's Republic of China

4. School of Computing and Mathematics, Charles Sturt UniversityAlburyNSW2640Australia

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2019.1690

Reference125 articles.

1. Structural and Functional Imaging

2. A general comparison of functional imaging in nuclear medicine with other modalities

3. The Role of Functional Imaging in Colorectal Cancer

4. Nuclear Imaging

5. An intelligent two‐phase fuzzy decision tree based clustering model for design of computer aided detection/diagnosis (CADe/CADx) system;Dhull A.;MAPAN,2017

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