Automatic motion compensation of free breathing acquired myocardial perfusion data by using independent component analysis

Wöllny, Gert and Kellman, Peter and Santos Lleo, Andres de and Ledesma Carbayo, María Jesús (2012). Automatic motion compensation of free breathing acquired myocardial perfusion data by using independent component analysis. "Medical Image Analysis", v. 16 (n. 5); pp. 1015-1028. ISSN 1361-8415. https://doi.org/10.1016/j.media.2012.02.004.

Description

Title: Automatic motion compensation of free breathing acquired myocardial perfusion data by using independent component analysis
Author/s:
  • Wöllny, Gert
  • Kellman, Peter
  • Santos Lleo, Andres de
  • Ledesma Carbayo, María Jesús
Item Type: Article
Título de Revista/Publicación: Medical Image Analysis
Date: July 2012
ISSN: 1361-8415
Volume: 16
Subjects:
Freetext Keywords: Perfusion, heart, registration, independent component analysis, motion compensation
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería Electrónica
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (8MB) | Preview

Abstract

Images acquired during free breathing using first-pass gadolinium-enhanced myocardial perfusion magnetic resonance imaging (MRI) exhibit a quasiperiodic motion pattern that needs to be compensated for if a further automatic analysis of the perfusion is to be executed. In this work, we present a method to compensate this movement by combining independent component analysis (ICA) and image registration: First, we use ICA and a time?frequency analysis to identify the motion and separate it from the intensity change induced by the contrast agent. Then, synthetic reference images are created by recombining all the independent components but the one related to the motion. Therefore, the resulting image series does not exhibit motion and its images have intensities similar to those of their original counterparts. Motion compensation is then achieved by using a multi-pass image registration procedure. We tested our method on 39 image series acquired from 13 patients, covering the basal, mid and apical areas of the left heart ventricle and consisting of 58 perfusion images each. We validated our method by comparing manually tracked intensity profiles of the myocardial sections to automatically generated ones before and after registration of 13 patient data sets (39 distinct slices). We compared linear, non-linear, and combined ICA based registration approaches and previously published motion compensation schemes. Considering run-time and accuracy, a two-step ICA based motion compensation scheme that first optimizes a translation and then for non-linear transformation performed best and achieves registration of the whole series in 32 ± 12 s on a recent workstation. The proposed scheme improves the Pearsons correlation coefficient between manually and automatically obtained time?intensity curves from .84 ± .19 before registration to .96 ± .06 after registration

More information

Item ID: 16009
DC Identifier: http://oa.upm.es/16009/
OAI Identifier: oai:oa.upm.es:16009
DOI: 10.1016/j.media.2012.02.004
Official URL: http://www.sciencedirect.com/science/article/pii/S1361841512000321
Deposited by: Memoria Investigacion
Deposited on: 26 Jun 2013 18:38
Last Modified: 21 Apr 2016 16:21
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM