An UNet-Based Brain Tumor Segmentation Framework via Optimal Mass Transportation Pre-processing

Jia Wei Liao, Tsung Ming Huang*, Tiexiang Li, Wen Wei Lin, Han Wang, Shing Tung Yau

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This article aims to build a framework for MRI images of brain tumor segmentation using the deep learning method. For this purpose, we develop a novel 2-Phase UNet-based OMT framework to increase the ratio of brain tumors using optimal mass transportation (OMT). Moreover, due to the scarcity of training data, we change the density function by different parameters to increase the data diversity. For the post-processing, we propose an adaptive ensemble procedure by solving the eigenvectors of the Dice similarity matrix and choosing the result with the highest aggregation probability as the predicted label. The Dice scores of the whole tumor (WT), tumor core (TC), and enhanced tumor (ET) regions for online validation computed by SegResUNet were 0.9214, 0.8823, and 0.8411, respectively. Compared with random crop pre-processing, OMT is far superior.

Original languageEnglish
Title of host publicationBrainlesion
Subtitle of host publicationGlioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 8th International Workshop, BrainLes 2022, Held in Conjunction with MICCAI 2022, Revised Selected Papers
EditorsSpyridon Bakas, Ujjwal Baid, Bhakti Baheti, Alessandro Crimi, Sylwia Malec, Monika Pytlarz, Maximilian Zenk, Reuben Dorent
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages13
ISBN (Print)9783031338410
Publication statusPublished - 2023
EventProceedings of the 8th International MICCAI Brainlesion Workshop, BrainLes 2022 - Singapore, Singapore
Duration: 2022 Sept 182022 Sept 22

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13769 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceProceedings of the 8th International MICCAI Brainlesion Workshop, BrainLes 2022


  • 2-Phase OMT framework
  • Brain Tumor Segmentation
  • Density function
  • Optimal Mass Transportation
  • UNet

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'An UNet-Based Brain Tumor Segmentation Framework via Optimal Mass Transportation Pre-processing'. Together they form a unique fingerprint.

Cite this