Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
368-02-010 ISMRM Abstract

Automated Segmentation of Thigh Muscles in Polyneuropathies

Primary: Analysis Methods - Segmentation and Detection
Secondary: Musculoskeletal - Muscle
368-02-010 · Segmentation for Musculoskeletal MRI Applications · Monday, 11 May, 9:15 AM–10:10 AM · Digital Posters Row I
Keywords: Quantitative MRI Deep learning Skeletal Muscle Segmentation NnU-Net Neuromuscular Disorders
Accepted
Kaizhong Shi1,2, Ying Wang1, Zichun Zhong3, Jesus E Fajardo1, Hasan Sawan1, Bo Hu4, Jun Li4, Yongsheng Chen 1,2
1Department of Neurology, Wayne State University School of Medicine, Detroit, United States of America
2Department of Biomedical Engineering, Wayne State University, Detroit, United States of America
3Department of Computer Science, Wayne State University, Detroit, United States of America
4Department of Neurology, Houston Methodist Research Institute, Houston, United States of America
Presenting Author: Yongsheng Chen

Synopsis

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References

1. Li J. Inherited neuropathies. Semin Neurol. 2012 Jul;32(3):204-214. doi:10.1055/s-0032-1329198. [doi]
2. Chen Y, Haacke EM, Li J. Peripheral nerve magnetic resonance imaging. F1000Res. 2019 Oct 28;8:F1000 Faculty Rev-1803. doi:10.12688/f1000research.19695.1. [doi]
3. Chen Y, Moiseev D, Kong WY, Bezanovski A, Li J. Automation of quantifying axonal loss in patients with peripheral neuropathies through deep learning derived muscle fat fraction. J Magn Reson Imaging. 2021 May;53(5):1539-1549. doi:10.1002/jmri.27508. [doi]
4. Ding J, Cao P, Chang H-C, Gao Y, Chan SHS, Vardhanabhuti V. Deep learning-based thigh muscle segmentation for reproducible fat fraction quantification using fat–water decomposition MRI. Insights Imaging. 2020;11(1):128. doi:10.1186/s13244-020-00946-8. [doi]
5. Agosti A, Shaqiri E, Paoletti M, Solazzo F, Bergsland N, Colelli G, Savini G, Muzic SI, Santini F, Deligianni X, Diamanti L, Monforte M, Tasca G, Ricci E, Bastianello S, Pichiecchio A. Deep learning for automatic segmentation of thigh and leg muscles. MAGMA. 2022 Jun;35(3):467-483. doi: 10.1007/s10334-021-00967-4. [doi]
6. Baudin P-Y, Balsiger F, Beck L, Boisserie J-M, Jouan S, Marty B, Reyngoudt H, Scheidegger O. A minimal annotation pipeline for deep learning segmentation of skeletal muscles. NMR Biomed. 2025 Jul;38(7):e70066. doi:10.1002/nbm.70066. [doi]
7. Chen Y, Baraz J, Xuan SY, Yang X, Castoro R, Xuan Y, Roth AR, Dortch RD, Li J. Multiparametric quantitative MRI of peripheral nerves in the leg: a reliability study. J Magn Reson Imaging. 2024 Feb;59(2):563-574. doi:10.1002/jmri.28778. [doi]

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http://echo.ismrm.org/p/ISMRM2026/368-02-010