Deep learning‐based segmentation of knee MRI for fully automatic subregional morphological assessment of cartilage tissues: Data from the Osteoarthritis Initiative
Author:
Affiliation:
1. Research Unit of Medical Imaging, Physics and Technology University of Oulu Oulu Finland
2. Department of Diagnostic Radiology Oulu University Hospital Oulu Finland
3. Ailean Technologies Oy Oulu Finland
Funder
Oulun Yliopisto
Sigrid Juséliuksen Säätiö
Jane ja Aatos Erkon Säätiö
KAUTE-Säätiö
Publisher
Wiley
Subject
Orthopedics and Sports Medicine
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/jor.25150
Reference43 articles.
1. Interobserver reproducibility of quantitative cartilage measurements: comparison of B-spline snakes and manual segmentation
2. Equivalence and precision of knee cartilage morphometry between different segmentation teams, cartilage regions, and MR acquisitions
3. Change in cartilage morphometry: a sample of the progression cohort of the Osteoarthritis Initiative
4. RyzhkovMDKnee Cartilage Segmentation Algorithms: A Critical Literature Review. [thesis]. Utrecht University; Utrecht University 2015.http://dspace.library.uu.nl/handle/1874/308831
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