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

Wöllny, Gert; Kellman, Peter; Santos Lleo, Andres de y 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.

Descripción

Título: Automatic motion compensation of free breathing acquired myocardial perfusion data by using independent component analysis
Autor/es:
  • Wöllny, Gert
  • Kellman, Peter
  • Santos Lleo, Andres de
  • Ledesma Carbayo, María Jesús
Tipo de Documento: Artículo
Título de Revista/Publicación: Medical Image Analysis
Fecha: Julio 2012
Volumen: 16
Materias:
Palabras Clave Informales: Perfusion, heart, registration, independent component analysis, motion compensation
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Ingeniería Electrónica
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

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

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ID de Registro: 16009
Identificador DC: http://oa.upm.es/16009/
Identificador OAI: oai:oa.upm.es:16009
Depositado por: Memoria Investigacion
Depositado el: 26 Jun 2013 18:38
Ultima Modificación: 21 Abr 2016 16:21
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