English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Magnetic resonance imaging used for diagnosis, localisation, and volume quantisation of tumours helps radiologists set treatment plans. Medical image segmentation is vital in detecting tumours. We propose a segmentation algorithm for identifying brain tumour regions using the fuzzy integrated active contour model. Fuzzy energy alterations define the contour and eliminate partial volume effects. We evaluated the algorithm on the BRATS 2012 and 2015 database and achieved an average dice score of 81% for the total abnormal region, including oedema, and 67% for an active tumour. This model is more robust than the classical snake methods based on the gradient.

Segmenting Brain Tumour Regions with Fuzzy Integrated Active Contours