Automatic brain tumour regions segmentation using modified U-Net

Keerati Kaewrak, John Soraghan, Gaetano Di Caterina, Derek Grose

Research output: Contribution to journalArticlepeer-review

16 Downloads (Pure)

Abstract

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.
Original languageEnglish
Pages (from-to)45-48
Number of pages4
JournalAcademic Journal for Thai Researchers in Europe
Volume1
Issue number1
DOIs
Publication statusPublished - 31 Dec 2020

Keywords

  • automatic segmentation
  • brain tumour
  • U-net

Fingerprint

Dive into the research topics of 'Automatic brain tumour regions segmentation using modified U-Net'. Together they form a unique fingerprint.

Cite this