2-Phase UNet-based OMT
BraTS 2021 Continuous Challenge database contains 2,040 brain images with 1,251 training images and 219 unlabeled brain image samples for validation.
The unreleased holdout testing data include the BraTS 2021 Challenge test data (BraTSTestingCohort), as well as two data sets: i) underrepresented SSA adult patient populations of brain diffuse glioma (SSAfricanData), and ii) pediatric population of diffuse intrinsic pontine glioma patients (PediatricData).
Members
Department of Applied Mathematics, National Yang Ming Chiao Tung University, Hsinchu 300, Taiwan
Department of Mathematics, National Taiwan Normal University, Taipei 116, Taiwan
School of Mathematics, Southeast University, Nanjing 211189, People’s Republic of China
Department of Mathematics, Harvard University, Cambridge, USA
Department of Mathematics, National Taiwan Normal University, Taipei 116, Taiwan
Department of Applied Mathematics, National Yang Ming Chiao Tung University, Hsinchu 300, Taiwan
Conference papers
Tsung-Ming Huang, Jia-Wei Liao, Wen-Wei Lin, and Hao-Ren Yao, A data pre-processing with mass-preserving optimal mass transportation for brain tumor segmentation, Journal of Decision Making and Healthcare, Vol. 1, pp 1–15, 2024, DOI: 10.69829/jdmh-024-0101-ta01
Jia-Wei Liao, Tsung-Ming Huang, Tiexiang Li, Wen-Wei Lin, Han Wang, and Shing-Tung Yau, An UNet-Based Brain Tumor Segmentation Framework via Optimal Mass Transportation Pre-processing, Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, BrainLes 2022, LNCS 13769, pp. 216–228, 2023. https://doi.org/10.1007/978-3-031-33842-7_19
Wen-Wei Lin, Tiexiang Li, Tsung-Ming Huang, Jia-Wei Lin, Mei-Heng Yueh and Shing-Tung Yau, A Two-Phase Optimal Mass Transportation Technique for 3D Brain Tumor Detection and Segmentation, Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2021. Lecture Notes in Computer Science, vol 12962, pp 400–409, Springer