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

We propose a multi-stage coarse-to-fine CNN-based framework, calledSkullEngine, for high-resolution segmentation and large-scale landmarkdetection through a collaborative, integrated, and scalable JSD model and threesegmentation and landmark detection refinement models. We evaluated ourframework on a clinical dataset consisting of 170 CBCT/CT images for the taskof segmenting 2 bones (midface and mandible) and detecting 175 clinicallycommon landmarks on bones, teeth, and soft tissues.

SkullEngine: A Multi-stage CNN Framework for Collaborative CBCT Image Segmentation and Landmark Detection