Automatic quadriceps and patellae segmentation of MRI with cascaded U 2 ‐Net and SASSNet deep learning model-Reference-Cited by-同舟云学术

Automatic quadriceps and patellae segmentation of MRI with cascaded U 2 ‐Net and SASSNet deep learning model

Published:2021-11-22 Issue:1 Volume:49 Page:443-460
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Medical Physics

Author:

Cheng Ruida¹,Crouzier Marion²³⁴,Hug François²⁵,Tucker Kylie³,Juneau Paul⁶,McCreedy Evan¹,Gandler William¹,McAuliffe Matthew J.¹,Sheehan Frances T.⁷

Affiliation:

1. Scientific Application Services (SAS) Office of Scientific Computing Services (OSCS) Office of Intramural Research Center of Information Technology, National Institutes of Health Bethesda Maryland

2. Movement, Interactions, Performance Laboratory University of Nantes Nantes France

3. School of Biomedical Sciences The University of Queensland Brisbane

4. Institut Universitaire de France Paris France

5. LAMHESS Université Côte d'Azur Nice France

6. NIH Library Office of Research Services National Institutes of Health Bethesda Maryland

7. Rehabilitation Medicine Department National Institutes of Health Clinical Center Bethesda Maryland

Funder

NIH Clinical Center

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.15335

Reference64 articles.

1. Automation of Quantifying Axonal Loss in Patients with Peripheral Neuropathies through Deep Learning Derived Muscle Fat Fraction

2. Automated Muscle Segmentation from Clinical CT Using Bayesian U-Net for Personalized Musculoskeletal Modeling

3. Automatic segmentation of all lower limb muscles from high-resolution magnetic resonance imaging using a cascaded three-dimensional deep convolutional neural network

4. Automated muscle segmentation from CT images of the hip and thigh using a hierarchical multi-atlas method

5. Fully automated patellofemoral MRI segmentation using holistically nested networks: Implications for evaluating patellofemoral osteoarthritis, pain, injury, pathology, and adolescent development

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