Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
564-06-005 ISMRM Abstract

OMT and tensor SVD based deep learning model for segmentation and predicting genetic markers of glioma: a multicenter study

Primary: Neuro - Tumors
Secondary: Analysis Methods - Classification and Prediction
564-06-005 · Segmentation for Neuro Applications · Wednesday, 13 May, 4:55 PM–5:50 PM · Digital Posters Row E
Keywords: Glioma IDH mutation Deep learning Optimal mass transport Algebraic pre-classification
Accepted
Zhengyang Zhu 1, Han Wang2, Huiquan Yang1, Yang Song3, Mengying Xu3, Xin Zhang1,4, Bing Zhang1
1Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
2Shanghai Institute for Mathematics and Interdisciplinary Sciences, Shanghai, China
3Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
4Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
Presenting Author: Zhengyang Zhu

Synopsis

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References

1. Louis DN, Perry A, Wesseling P, Brat DJ, Cree IA, Figarella-Branger D, Hawkins C, Ng HK, Pfister SM, Reifenberger G, Soffietti R, von Deimling A, Ellison DW. The 2021 WHO Classification of Tumors of the Central Nervous System: a summary. Neuro Oncol. 2021 Aug 2;23(8):1231-1251. doi: 10.1093/neuonc/noab106. PMID: 34185076. [doi] [pmid]
2. Lin WW, Lin JW, Huang TM, Li T, Yueh MH, Yau ST. A novel 2-phase residual U-net algorithm combined with optimal mass transportation for 3D brain tumor detection and segmentation. Sci Rep. 2022 Apr 19;12(1):6452. doi: 10.1038/s41598-022-10285-x. [doi]
3. Choi YS, Bae S, Chang JH, Kang SG, Kim SH, Kim J, Rim TH, Choi SH, Jain R, Lee SK. Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics. Neuro Oncol. 2021 Feb 25;23(2):304-313. doi: 10.1093/neuonc/noaa177. PMID: 32706862. [doi] [pmid]
4. van der Voort SR, Incekara F, Wijnenga MMJ, Kapsas G, Gahrmann R, Schouten JW, Nandoe Tewarie R, Lycklama GJ, De Witt Hamer PC, Eijgelaar RS, French PJ, Dubbink HJ, Vincent AJPE, Niessen WJ, van den Bent MJ, Smits M, Klein S. Combined molecular subtyping, grading, and segmentation of glioma using multi-task deep learning. Neuro Oncol. 2023 Feb 14;25(2):279-289. doi: 10.1093/neuonc/noac166. PMID: 35788352. [doi] [pmid]
5. Zhu Z, Shen J, Liang X, Zhou J, Liang J, Ni L, Wang H, Ye M, Chen S, Yang H, Chen Q, Li X, Zhang W, Lu J, Ge D, Fu L, Zhu Y, Zhang X, Sun Y, Zhang B. Radiomics for predicting grades, isocitrate dehydrogenase mutation, and oxygen 6-methylguanine-DNA methyltransferase promoter methylation of adult diffuse gliomas: combination of structural MRI, apparent diffusion coefficient, and susceptibility-weighted imaging. Quant Imaging Med Surg. 2024 Dec 5;14(12):9276-9289. doi: 10.21037/qims-24-1110. Epub 2024 Nov 29. PMID: 39698654. [doi] [pmid]

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http://echo.ismrm.org/p/ISMRM2026/564-06-005