Automatic brain tumour regions segmentation using modified U-Net

Kaewrak, Keerati and Soraghan, John and Di Caterina, Gaetano and Grose, Derek (2020) Automatic brain tumour regions segmentation using modified U-Net. Academic Journal for Thai Researchers in Europe, 1 (1). pp. 45-48. ISSN 2730-2784 (

[thumbnail of Kaewrak-etal-AJTRE-2020-Automatic-brain-tumour-regions-segmentation-using-modified]
Text. Filename: Kaewrak_etal_AJTRE_2020_Automatic_brain_tumour_regions_segmentation_using_modified.pdf
Final Published Version
License: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 logo

Download (383kB)| Preview


Early diagnosis is an important key for brain tumour patients' survival. The segmentation of the tumour regions is done manually by the experts and it is time-consuming. In this work, we present a novel network architecture that automatically segments the whole tumour regions and intra-tumour structures (edema, enhancing tumour, necrotic and non-enhancing tumour). We evaluated the results using dice similarity coefficient and obtained promising results.