Automated cartilage segmentation and quantification using 3D ultrashort echo time (UTE) cones MR imaging with deep convolutional neural networks-Reference-Cited by-同舟云学术

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Automated cartilage segmentation and quantification using 3D ultrashort echo time (UTE) cones MR imaging with deep convolutional neural networks

Published:2021-03-30 Issue:10 Volume:31 Page:7653-7663
ISSN:0938-7994
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Xue Yan-Ping,Jang Hyungseok,Byra Michal,Cai Zhen-Yu,Wu Mei,Chang Eric Y.,Ma Ya-Jun,Du Jiang

Funder

National Institute of Arthritis and Musculoskeletal and Skin Diseases

the VA Clinical Science Research & Development Service

GE Healthcare

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00330-021-07853-6.pdf

Reference46 articles.

1. Saarakkala S, Julkunen P, Kiviranta P, Mäkitalo J, Jurvelin JS, Korhonen RK (2010) Depth-wise progression of osteoarthritis in human articular cartilage: investigation of composition, structure, and biomechanics. Osteoarthritis Cartilage 18:73–81

2. Stehling C, Liebl H, Krug R et al (2010) Patellar cartilage: T2 values and morphologic abnormalities at 3.0-T MR imaging in relation to physical activity in asymptomatic subjects from the osteoarthritis initiative. Radiology 254:509–520

3. Hu J, Zhang Y, Duan C, Peng X, Hu P, Lu H (2017) Feasibility study for evaluating early lumbar facet joint degeneration using axial T1ρ, T2, and T2* mapping in cartilage. J Magn Reson Imaging 46:468–475

4. Su F, Hilton JF, Nardo L et al (2013) Cartilage morphology and T1ρ and T2 quantification in ACL reconstructed knees: a 2-year follow-up. Osteoarthritis Cartilage 21:1058–1067

5. Li X, Cheng J, Lin K et al (2011) Quantitative MRI using T1ρ and T2 in human osteoarthritic cartilage specimens: correlation with biochemical measurements and histology. Magn Reson Imaging 29:324–334

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