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

Over time, Augmented Reality (AR) based technology becomes not being properly to implement with oral and maxillofacial surgery to visualise the narrow area spot in jaw surgery as blood vassals and root canals in these types of surgeries. Image registration is considered the major limitation of using the AR in these types of surgeries and reduces the accuracy of visualising the narrow areas. In this research, we propose a Correntropy based scale ICP algorithm as a solution to improve the image registration during jaw surgery. Correntropy is considered here to minimise the error metric of the ICP algorithm instead of the Euclidean distance measurement compared to the state-of-the-art solution. This led to decrease the registration error, increase the video accuracy and reduce the processing time simultaneously. The proposed system consists of Enhanced Tracking Learning Detection (TLD), which is used as an occlusion removal featured algorithm in the intra-operative stage of the AR-based jaw surgery system. In this research, a Modified Correntropy-based enhanced ICP (MCbeICP) algorithm is proposed for the system’s pose-refinement phase. Moreover, this proposed algorithm (MCbeICP) has a new function to process the point set registration with great noises and outliers. It eliminates the poor performance of the ICP algorithm of the noisy point set. Furthermore, the ICP algorithm considers the scale factor to register the point with different scales of the real-time video and the sample models. Additionally, this method improves the result of the pose refinement stage in terms of registration accuracy and processing time. By this method, the pose refinement stage gives an improved result in terms of registration accuracy and processing time. The samples, which were taken from the upper (maxillary) and the lower (mandible) jaw bone show that the proposed algorithm provides a significant accuracy improvement in alignment to 0.21- 0.29 mm from 0.23 to 0.35 mm and an increment in processing time from 8 to 12 frames per second (fs/s) to 10-14 fs/s compared to the result provided by state of the art. The proposed augmented reality (AR) system is focused on the overlay accuracy and processing time. Finally, this study addressed the limitation of Image registration with AR using modified Correntropy-based enhanced ICP algorithm to implement oral and maxillofacial surgery successfully.

Augmented reality for visualization the narrow areas in jaw surgery: modified Correntropy based enhanced ICP algorithm