A novel enhanced intensity-based automatic registration: Augmented reality for visualization and localization cancer tumors

Wilvertson Tan, Abeer Alsadoon, P. W.C. Prasad, Shahd Al-Janabi, Sami Haddad, Haritha Sallepalli Venkata, Ahmad Alrubaie

Research output: Contribution to journalArticle


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.
Original languageEnglish
Article numbere2043
Pages (from-to)1-15
Number of pages15
JournalInternational Journal of Medical Robotics and Computer Assisted Surgery
Issue number2
Early online date01 Nov 2019
Publication statusPublished - Apr 2020


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