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Clinical evaluation of fully automated thigh muscle and adipose tissue segmentation using a U-Net deep learning architecture in context of osteoarthritic knee pain

Jana Kemnitz, Christian F. Baumgartner, F. Eckstein, Akshay Chaudhari, A. Ruhdorfer, W. Wirth, Sebastian K. Eder, Ender Konukoğlu

Magnetic Resonance Materials in Physics Biology and Medicine · 2019 · 50 citations · 33 references

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References

33

Use of 2D U-Net Convolutional Neural Networks for Automated Cartilage and Meniscus Segmentation of Knee MR Imaging Data to Determine Relaxometry and Morphometry

Berk Norman, Valentina Pedoia, Sharmila Majumdar · Radiology · 2018 · 419 citations · Full text

Muscle and external load contribution to knee joint contact loads during normal gait

C.R. Winby, David G. Lloyd, Thor F. Besier et al. · Journal of Biomechanics · 2009 · 366 citations

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Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging

Fang Liu, Zhaoye Zhou, Hyungseok Jang et al. · Magnetic Resonance in Medicine · 2017 · 317 citations · Full text

Automatic and quantitative assessment of regional muscle volume by multi‐atlas segmentation using whole‐body water–fat MRI

Anette Karlsson, Johannes Rosander, Thobias Romu et al. · Journal of Magnetic Resonance Imaging · 2014 · 213 citations

Pathobiology of obesity and osteoarthritis: integrating biomechanics and inflammation

RitaI. Issa, TimothyM. Griffin · Pathobiology of Aging & Age-related Diseases · 2012 · 173 citations · Full text

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