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A novel enhanced intensity-based automatic registration: Augmented reality for visualization and localization cancer
Wilvertson Tan1, Abeer Alsadoon1, P W C Prasad1
1Charles Sturt University Study Centre, Sydney, Australia.
Abstract:
The purpose of this study is to replace the manual process (selecting the landmarks on mesh and anchor points on the video) by Intensity-based Automatic Registration method to reach registration accuracy and low processing time. The proposed system consists of an Enhanced Intensity-based Automatic Registration (EIbAR) using Modified Zero Normalized Cross Correlation (MZNCC) algorithm. The proposed system was implemented on videos of breast cancer tumors. Results showed that the proposed algorithm-as compared to a reference-improved registration accuracy by an average of 2 mm. In addition, the proposed algorithm-as compared to a reference-reduced the number of pixel matching, thereby reducing processing time on the video by an average of 22 ms/frame. The proposed system can, thus, provide an acceptable accuracy and processing time during scene augmentation of videos, which provides a seamless use of augmented-reality for surgeons in visualizing cancer tumors.

