Deep learning prediction of diffusion MRI data with microstructure-sensitive loss functions-Reference-Cited by-同舟云学术

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Deep learning prediction of diffusion MRI data with microstructure-sensitive loss functions

Published:2023-04 Issue: Volume:85 Page:102742
ISSN:1361-8415
Container-title:Medical Image Analysis
language:en
Short-container-title:Medical Image Analysis

Author:

Chen Geng^ORCID,Hong Yoonmi,Huynh Khoi Minh,Yap Pew-Thian^ORCID

Funder

National Institute of Biomedical Imaging and Bioengineering

National Institutes of Health

National Institute of Mental Health

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference57 articles.

1. Tensorflow: A system for large-scale machine learning;Abadi,2016

2. MoDL-MUSSELS: model-based deep learning for multishot sensitivity-encoded diffusion MRI;Aggarwal;IEEE Trans. Med. Imaging,2019

3. How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging;Andersson;NeuroImage,2003

4. An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging;Andersson;NeuroImage,2016

5. Probabilistic tractography for topographically organized connectomes;Aydogan,2016

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An efficient penalty function method for scenario-based uncertainty quantification problems;Journal of Vibration and Control;2024-01-23

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