Keywords

medical imaging; segmentation

Abstract

Cardiac strains are a promising tool for analyzing local cardiac function in the left ventricle (LV). The displacement field of the LV is necessary to compute these strains. Displacement ENcoding with Stimulated Echoes (DENSE) Magnetic Resonance Imaging (MRI) is a powerful research imaging sequence that encodes voxel-wise displacement information in scanned slices. To extract displacements from DENSE MRI, an accurate segmentation of the LV is required. This thesis proposes a novel method of segmentation that utilizes a seeded growth algorithm and iterative refinement to produce a high-quality segmentation of the LV in DENSE MRI. This segmentation algorithm is applied to a deforming cardiac phantom to examine extracted displacements as well as cardiac torsion. The produced segmentation is high in quality, containing few to no erroneous voxels. The displacements extracted from the phantom also agree well with the analytical displacements used to construct the phantom.

Thesis Completion Year

2026

Thesis Completion Semester

Summer

Thesis Chair

Perotti, Luigi

College

College of Engineering and Computer Science

Department

Department of Mechanical and Aerospace Engineering

Thesis Discipline

Mechanical Engineering

Language

English

Access Status

Campus Access

Length of Campus Access

3 years

Campus Location

Orlando (Main) Campus

Download

Available for download on Wednesday, August 15, 2029

Share

COinS
 

Accessibility Statement

This item was created or digitized prior to April 24, 2027, or is a reproduction of legacy media created before that date. It is preserved in its original, unmodified state specifically for research, reference, or historical recordkeeping. In accordance with the ADA Title II Final Rule, the University Libraries provides accessible versions of archival materials upon request. To request an accommodation for this item, please submit an accessibility request form.

Rights Statement

In Copyright