In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

Mahmut Unan

will defend his dissertation

3D Reconstruction of Tubular Structures Using MRI Projection Images

Abstract

After imaging information became available in digital form, acquiring volumetric data technics evolved. 3D reconstruction is mostly performed using multislice stack images. The objective of this dissertation is to introduce a simple magnetic resonance technique for imaging tubular structures, such as blood vessels and catheters, and their 3D reconstruction. This study includes three major chapters: one simulation and two experiments with MRI projection images. First, a MATLAB simulation was created to analyze the reconstruction process; it is tested with different shapes of the structures and different numbers of the projections. Second, triplanar projection imaging was evaluated on a phantom filled with a T1-shortening, Gd-based contrast agent embedded into a lipid matrix. The object is reconstructed from three mutually orthogonal projections of the volume that contain the structure of interest. The projected structures of the object were segmented out on each projection, back-projected to generate the segmented tubular object, and mesh-rendered in 3D. The accuracy of this approach was investigated by comparing the mesh-rendered tubular structure generated from projections with the mesh extracted from a multislice set of images of the same volume. Third, Inverse Radon Transform was implemented for 3D reconstruction of complex helical tubular structure from multiple radially deployed (oblique) projections. To compute the correctness of the 3D reconstruction processes, we compared the resulting meshes with the multislice-rendered meshes. Hausdorff distance and Point Cloud Comparison methods were used to evaluate the reconstruction error. The average error was less than 1 pixel for the triplanar projection images, and it was less than 2 pixels for the oblique orientation projection images. With further optimization and reduction of acquisition time, this method can be used for 3D fast imaging of interventional tools or segments of blood vessels with applications in interventional MRI.

Date: Monday, March 26, 2018
Time: 11:00 AM
Place: PGH 550
Advisor: Dr. Nikolaos V. Tsekos

Faculty, students, and the general public are invited.