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Updated: Oct 10, 2026
Reproducible 3D Glioblastoma Migration Assay with Magnetic Nanoparticle Mediated Spheroid Localization Under Hypoxic Conditions
Published on: May 12, 2026
Localization-guided segmentation of Gliomas via 3D ReFusionNet
Ling Chen1, Jinzhu Chang2, Qi Zhang1
1Department of Radiology, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, China.
Purpose:
This study presents a localization-guided two-stage 3D framework for the automated segmentation of brain tumors.
Methods:
ReFusionNet first estimates a single region of interest containing the tumor-bearing region and then segments the whole tumor, tumor core, and enhancing tumor within the localized volume. The framework was evaluated on the UPENN-GBM and BraTS 2021 datasets using recall, precision, Dice score, and the 95th-percentile Hausdorff distance (HD95).
Results:
On the UPENN-GBM test set, ReFusionNet-A achieved Dice scores of 0.90, 0.81, and 0.77 for the whole tumor, tumor core, and enhancing tumor, respectively. Its corresponding HD95 values were 11.68, 21.53, and 10.49. The localization-guided models generally showed higher precision and lower HD95 values for selected regions, but lower recall and Dice scores occurred in some tumor-core and enhancing-tumor comparisons. On BraTS 2021, ReFusionNet-C achieved competitive Dice scores, although its HD95 values were not the lowest among the models compared.
Conclusion:
ReFusionNet achieved competitive segmentation performance on the evaluated public datasets. Its principal observed advantages were higher precision and lower HD95 values in selected tumor regions, while performance gains were not uniform across all metrics.
