Improved myelin water fraction mapping with deep neural networks using synthetically generated 3D data

Author:

Vasylechko Serge DidenkoORCID,Warfield Simon K.ORCID,Kurugol SilaORCID,Afacan OnurORCID

Funder

National Institute of Biomedical Imaging and Bioengineering

U.S. National Library of Medicine

National Multiple Sclerosis Society

National Institutes of Health

United States-Israel Binational Science Foundation

National Institute of Neurological Disorders and Stroke

National Institute of Diabetes and Digestive and Kidney Diseases

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

Reference48 articles.

1. Fast myelin water fraction estimation using 2D multislice CPMG;Akhondi-Asl;Magn. Reson. Med.,2016

2. T 2-relaxometry for myelin water fraction extraction using wald distribution and extended phase graph;Akhondi-Asl,2014

3. MRI-based myelin water imaging: a technical review;Alonso-Ortiz;Magn. Reson. Med.,2015

4. A learning strategy for contrast-agnostic MRI segmentation;Billot,2020

5. Partial volume segmentation of brain MRI scans of any resolution and contrast;Billot,2020

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