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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Brain tumor is one of the most high-risk cancers which causes the 5-yearsurvival rate of only about 36%. Accurate diagnosis of brain tumor is criticalfor the treatment planning. However, complete data are not always available inclinical scenarios. In this paper, we propose a novel brain tumor segmentationnetwork to deal with the missing data issue. To compensate for missing data, wepropose to use a conditional generator to generate the missing modality underthe condition of the available modalities. As the multi-modality has a strongcorrelation in tumor region, we design a correlation constraint network toleverage the multi-source information. On the one hand, the correlationconstraint network can help the conditional generator to generate the missingmodality which should keep the multi-source correlation with the availablemodalities. On the other hand, it can guide the segmentation network to learnthe correlated feature representations to improve the segmentation performance.The proposed network consists of a conditional generator, a correlationconstraint network and a segmentation network. We carried out extensiveexperiments on BraTS 2018 dataset to evaluate the proposed method.Theexperimental results demonstrate the importance of the proposed components andthe superior performance of the proposed method com-pared with thestate-of-the-art methods

Conditional generator and multi-sourcecorrelation guided brain tumor segmentation with missing MR modalities