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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

This paper analyzes the use of 3D Convolutional Neural Networks for braintumor segmentation in MR images. We address the problem using three differentarchitectures that combine fine and coarse features to obtain the finalsegmentation. We compare three different networks that use multi-resolutionfeatures in terms of both design and performance and we show that they improvetheir single-resolution counterparts.

3D Convolutional Neural Networks for Brain Tumor Segmentation: A Comparison of Multi-resolution Architectures