Fluorescence to color feature-based image registration for medical augmented reality

Tri Quang; Mingzhou Zhou; Francis Papay; Yang Liu

doi:10.1109/ISSPIT.2018.8705148

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Conference proceeding

Fluorescence to color feature-based image registration for medical augmented reality

Tri Quang, Mingzhou Zhou, Francis Papay and Yang Liu

2018 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Vol.2019-, pp.1-6

12/2018

DOI: 10.1109/ISSPIT.2018.8705148

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Abstract

In recent years, augmented reality with fluorescence imaging has attracted significant attention for computer aided surgeries. Overlaying functional information acquired from fluorescence images on the anatomical information of color images offers intuitive surgical guidance. In this study, we investigate the feasibility of SIFT, SURF, BRISK, and ORB algorithms in registration of fluorescence and color reflectance images for intraoperative augmented reality and surgical guidance. We have further demonstrated the potential of a new registration method combining SURF, BRISK and ORB which showed improved registration accuracy. Several sets of experiments were performed on phantoms, biological tissues with fluorescently labeled targets to evaluate the performance of various algorithms. We have demonstrated the feasibility of applying feature-based registration methods in fluorescence-to-color image registration for intraoperative augmented reality. We have also demonstrated the potential of a new featurebased image registration method combining BRISK, SURF, and ORB.

Augmented Reality

Computer Vision

Fluorescence

Feature extraction

feature-based registration

Image color analysis

Image registration

Imaging

intraoperative imaging

Reflectivity

Signal processing algorithms

surgical guidance

Details

Title: Subtitle: Fluorescence to color feature-based image registration for medical augmented reality
Creators: Tri Quang - University of Akron
Mingzhou Zhou - University of Akron
Francis Papay - Cleveland Clinic
Yang Liu - University of Akron
Resource Type: Conference proceeding
Publication Details: 2018 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Vol.2019-, pp.1-6
DOI: 10.1109/ISSPIT.2018.8705148
Publisher: IEEE
Language: English
Date published: 12/2018
Academic Unit: Electrical and Computer Engineering
Record Identifier: 9984197346702771

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