Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
561-02-012 ISMRM Abstract

Adaptive ROI Extraction and 3D Consistency Voting for Robust Automated Water–Fat Classification in Musculoskeletal MRI

Primary: Musculoskeletal - Whole Joint
Secondary: Contrast Mechanisms - Fat & Fat/Water Separation
561-02-012 · Classification and Analysis in the Body · Wednesday, 13 May, 9:15 AM–10:10 AM · Digital Posters Row B
Keywords: Dixon technique Musculoskeletal MRI Water fat classification Anatomical adaptability 3D consistency voting
Accepted
Junying Cheng 1, MENGZHU WANG2, Qichang Fu1, Li Zhu1, zhongbiao xu3, Zhifeng Chen4, Tan Yuan1, Yanqiu Feng5, Yong Zhang1
1Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
2MR Research Collaboration Team, Siemens Healthineers Ltd., Beijing, China
3Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, GuangDong, Guangzhou, China
4Neusoft Medical Systems Co., Ltd., Hangzhou, China
5School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
Presenting Author: Junying Cheng

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References

1. Lecouvet F. E. (2016). Whole-Body MR Imaging: Musculoskeletal Applications. Radiology, 279(2), 345–365. https://doi.org/10.1148/radiol.2016142084 [doi]
2. Flores, D. V., Mejía Gómez, C., Estrada-Castrillón, M., Smitaman, E., & Pathria, M. N. (2018). MR Imaging of Muscle Trauma: Anatomy, Biomechanics, Pathophysiology, and Imaging Appearance. Radiographics : a review publication of the Radiological Society of North America, Inc, 38(1), 124–148. https://doi.org/10.1148/rg.2018170072 [doi]
3. Gollifer, R. M., Bray, T. J. P., Kruezi, A., Markus, J., Choida, V., Hall-Craggs, M. A., & Bainbridge, A. (2023). A multiparametric alternative to short inversion-time inversion recovery for imaging inflammation: T2water and fat fraction measurement using chemical shift-encoded turbo spin-echo MRI. Magnetic resonance in medicine, 90(3), 1010–1024. https://doi.org/10.1002/mrm.29689 [doi]
4. Chen, Y., Zhang, X., Li, M., Zhong, L., Ding, Y., Zhang, Y., Du, X., Mo, X., Chen, J., Chen, Q., Huang, W., Zhong, S., & Zhang, X. (2022). Quantitative MR evaluation of the infrapatellar fat pad for knee osteoarthritis: using proton density fat fraction and T2* relaxation based on DIXON. European radiology, 32(7), 4718–4727. https://doi.org/10.1007/s00330-022-08561-5 [doi]
5. Bachrata, B., Trattnig, S., & Robinson, S. D. (2022). Quantitative susceptibility mapping of the head-and-neck using SMURF fat-water imaging with chemical shift and relaxation rate corrections. Magnetic resonance in medicine, 87(3), 1461–1479. https://doi.org/10.1002/mrm.29069 [doi]
6. Berkarda, Z., Wiedemann, S., Wilpert, C., Strecker, R., Koerzdoerfer, G., Nickel, D., Bamberg, F., Benndorf, M., Mayrhofer, T., Russe, M. F., Weiss, J., & Diallo, T. D. (2024). Deep learning reconstructed T2-weighted Dixon imaging of the spine: Impact on acquisition time and image quality. European journal of radiology, 178, 111633. https://doi.org/10.1016/j.ejrad.2024.111633 [doi]
7. Pezeshk, P., Alian, A., & Chhabra, A. (2017). Role of chemical shift and Dixon based techniques in musculoskeletal MR imaging. European journal of radiology, 94, 93–100. https://doi.org/10.1016/j.ejrad.2017.06.011 [doi]
8. Jungmann, P. M., Agten, C. A., Pfirrmann, C. W., & Sutter, R. (2017). Advances in MRI around metal. Journal of magnetic resonance imaging, 46(4), 972–991. https://doi.org/10.1002/jmri.25708 [doi]
9. Del Grande, F., Santini, F., Herzka, D. A., Aro, M. R., Dean, C. W., Gold, G. E., & Carrino, J. A. (2014). Fat-suppression techniques for 3-T MR imaging of the musculoskeletal system. Radiographics, 34(1), 217–233. https://doi.org/10.1148/rg.341135130 [doi]
10. Eggers, H., & Börnert, P. (2014). Chemical shift encoding-based water-fat separation methods. Journal of magnetic resonance imaging, 40(2), 251–268. https://doi.org/10.1002/jmri.24568 [doi]
11. Otsu N. A threshold selection method from gray-level histograms[J]. Automatica, 1975, 11(285-296): 23-27.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/561-02-012