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A novel enhanced intensity‐based automatic registration: Augmented reality for visualization and localization cancer tumors
Author(s) -
Tan Wilvertson,
Alsadoon Abeer,
Prasad P.W.C.,
AlJanabi Shahd,
Haddad Sami,
Venkata Haritha Sallepalli,
Alrubaie Ahmad
Publication year - 2020
Publication title -
the international journal of medical robotics and computer assisted surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 53
eISSN - 1478-596X
pISSN - 1478-5951
DOI - 10.1002/rcs.2043
Subject(s) - computer science , augmented reality , computer vision , artificial intelligence , image registration , visualization , matching (statistics) , frame (networking) , process (computing) , pixel , template matching , intensity (physics) , image (mathematics) , medicine , telecommunications , physics , pathology , quantum mechanics , operating system
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.