A Sparsely Distributed Intra-cardial Ultrasonic Array for Real-Time Endocardial Mapping

Alon Baram, Hayit Greenspan, Zvi Freidman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Cardiac arrhythmia is the clinical term for the family of diseases wherein the heart beats irregularly. Of these conditions, atrial fibrillation (AF) is one of the most prevalent and afflicts about 25% of the population of European descent over the age of 40. This condition leads to congestive heart failure, increases the risk of stroke five fold, impairs quality of life, causes hundreds of thousands hospitalizations in the US alone and is linked with increased mortality. Electrical pulmonary vein isolation (PVI) from the left atrial (LA) body is performed using ablation for treating AF. This and many other minimally invasive catheterizations, require real-time visualization and tracking of the LA endocardial surface. We propose a novel catheter based system incorporating ultrasound transducers mounted on a set of splines, and an algorithm capable of real time reconstruction of the chamber endocardial boundary, with almost no need for catheter movement or rotation. Unlike traditional ultrasound arrays, this catheter employs a small number of sparsely scattered transducer elements, far less than required by the Nyquist criterion, and a spherical field of view. Our concept had very little theoretical and practical known guarantees. We have developed novel methods to extract the blood pool location in space and validated them against reflecting tissue producing high contrast images of the boundary. We further validated our methods by extensive in-silico simulation studies and hardware phantom experiments. A prototype system is currently being built, following initial animal experimentation that further support the feasibility of this system in-vivo.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings
EditorsDinggang Shen, Pew-Thian Yap, Tianming Liu, Terry M. Peters, Ali Khan, Lawrence H. Staib, Caroline Essert, Sean Zhou
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages9
ISBN (Print)9783030322533
StatePublished - 2019
Event22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019 - Shenzhen, China
Duration: 13 Oct 201917 Oct 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11768 LNCS


Conference22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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