Automatic segmentation of high- and low-field knee MRIs using knee image quantification with data from the osteoarthritis initiative-Reference-Cited by-同舟云学术

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Automatic segmentation of high- and low-field knee MRIs using knee image quantification with data from the osteoarthritis initiative

Published:2015-04-20 Issue:2 Volume:2 Page:024001
ISSN:2329-4302
Container-title:Journal of Medical Imaging
language:en
Short-container-title:J. Med. Imag

Author:

Dam Erik B.¹,Lillholm Martin²,Marques Joselene²,Nielsen Mads³

Affiliation:

1. Biomediq A/S, Fruebjergvej 3, Copenhagen OE 2100, DenmarkbThe D-BOARD European Consortium for Biomarker Discovery

2. Biomediq A/S, Fruebjergvej 3, Copenhagen OE 2100, Denmark

3. Biomediq A/S, Fruebjergvej 3, Copenhagen OE 2100, DenmarkcUniversity of Copenhagen, Department of Computer Science, Sigurdsgade 31, København N 2200, Denmark

Publisher

SPIE-Intl Soc Optical Eng

Subject

Radiology Nuclear Medicine and imaging

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2. Fair AI-powered orthopedic image segmentation: addressing bias and promoting equitable healthcare;Scientific Reports;2024-07-12

3. Association of smoking with cartilage loss of knee osteoarthritis: data from two longitudinal cohorts;BMC Musculoskeletal Disorders;2023-10-13

4. Dual output feature fusion networks for femoral segmentation and quantitative analysis of the knee joint;Medical Physics;2023-08-26

5. A Comprehensive Review on MRI-based Knee Joint Segmentation and Analysis Techniques;Current Medical Imaging Formerly Current Medical Imaging Reviews;2023-07-07

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