Developing New Image Registration Techniques and 3D Displays for Neuroimaging and Neurosurgery

Date

2013-04-05
Language
American English

Embargo Lift Date

Department

Committee Members

Degree

Degree Year

Department

Grantor

Journal Title

Journal ISSN

Volume Title

Found At

Office of the Vice Chancellor for Research

Abstract

Image guided surgery requires that the pre-operative data used for planning the surgery should be aligned with the patient during surgery. For this surgical application a fast, effective volume registration algorithm is needed. In addition, such an algorithm can also be used to develop surgical training presentations. This research extends existing methods and techniques to improve convergence and speed of execution. The aim is to find the most promising speed improvements while maintaining accuracy to best fit the neurosurgery application. In the recent phase, we focus on feature extraction and the time-accuracy trade-off. Medical image volumes acquired from MRI or CT medical imaging scans provided by the Indiana University School of Medicine were used as test image cases. Additional synthetic data with ground truth is developed by the Informatics students. The speed-enhancements to the registration are compared against the ground truth evaluated with mean squared error metrics. Algorithm execution time with and without speed improvement is measured on standard personal computer (PC) hardware. Additionally, the informatics students are developing a 3D movie that shows the surgical and preoperative data overlay, which presents the results of the speed improvements from the remaining students’ work. Our testing indicates that an intelligent subset of the data points that are needed for registration should improve the speed significantly. Preliminary results show that even though image registration in real-time is a challenging task for real time neurosurgery applications, intelligent preprocessing provides a promising solution. Final results will be available at paper presentation.

Description

poster abstract

item.page.description.tableofcontents

item.page.relation.haspart

Cite As

Zheng, Yuese, Yici Jing, Thanh Nguyen, Sarah Zajac, Jacob Wright, and Robin Catania. (2013, April 5). Developing New Image Registration Techniques and 3D Displays for Neuroimaging and Neurosurgery. Poster session presented at IUPUI Research Day 2013, Indianapolis, Indiana.

ISSN

Publisher

Series/Report

Sponsorship

Major

Extent

Identifier

Relation

Journal

Rights

Source

Alternative Title

Type

Poster

Number

Volume

Conference Dates

Conference Host

Conference Location

Conference Name

Conference Panel

Conference Secretariat Location

Version

Full Text Available at

This item is under embargo {{howLong}}