Related Experiment Video
Updated: May 3, 2026

Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
Published on: July 20, 2022
A POINT-CORRESPONDENCE APPROACH TO DESCRIBING THE DISTRIBUTION OF IMAGE FEATURES ON ANATOMICAL SURFACES, WITH
Gregory Gardner1, Alan Morris2, Koji Higuchi3
1Scientific Computing and Imaging Institute University of Utah, Salt Lake City, UT, USA ; CARMA Center, University of Utah, Salt Lake City, UT, USA.
Abstract:
This paper describes a framework for summarizing and comparing the distributions of image features on anatomical shape surfaces in populations. The approach uses a point-based correspondence model to establish a mapping among surface positions and may be useful for anatomy that exhibits a relatively high degree of shape variability, such as cardiac anatomy. The approach is motivated by the MRI-based study of diseased, or fibrotic, tissue in the left atrium of atrial fibrillation (AF) patients, which has been difficult to measure quantitatively using more established image and surface registration techniques. The proposed method is to establish a set of point correspondences across a population of shape surfaces that provides a mapping from any surface to a common coordinate frame, where local features like fibrosis can be directly compared. To establish correspondence, we use a previously-described statistical optimization of particle-based shape representations. For our atrial fibrillation population, the proposed method provides evidence that more intense and widely distributed fibrosis patterns exist in patients that do not respond well to radiofrequency ablation therapy.
More Related Videos
09:17High-Resolution Endocardial and Epicardial Optical Mapping in a Sheep Model of Stretch-Induced Atrial Fibrillation
Published on: July 29, 2011
05:23Author Spotlight: Noninvasive Cerebral Blood Flow Determination in Human Functional Brain Region for Diagnosis of Neurological Disorders
Published on: May 31, 2024