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

In the gastrointestinal (GI) tract endoscopy field, ingestible wirelesscapsule endoscopy is considered as a minimally invasive novel diagnostictechnology to inspect the entire GI tract and to diagnose various diseases andpathologies. Since the development of this technology, medical device companiesand many groups have made significant progress to turn such passive capsuleendoscopes into robotic active capsule endoscopes to achieve almost allfunctions of current active flexible endoscopes. However, the use of roboticcapsule endoscopy still has some challenges. One such challenge is the preciselocalization of such active devices in 3D world, which is essential for aprecise three-dimensional (3D) mapping of the inner organ. A reliable 3D map ofthe explored inner organ could assist the doctors to make more intuitive andcorrect diagnosis. In this paper, we propose to our knowledge for the firsttime in literature a visual simultaneous localization and mapping (SLAM) methodspecifically developed for endoscopic capsule robots. The proposed RGB-DepthSLAM method is capable of capturing comprehensive dense globally consistentsurfel-based maps of the inner organs explored by an endoscopic capsule robotin real time. This is achieved by using dense frame-to-model camera trackingand windowed surfelbased fusion coupled with frequent model refinement throughnon-rigid surface deformations.

A Non-Rigid Map Fusion-Based RGB-Depth SLAM Method for Endoscopic Capsule Robots