Literature DB >> 9873904

Motion and deformation tracking for short-axis echo-planar myocardial perfusion imaging.

G Z Yang1, P Burger, J Panting, P D Gatehouse, D Rueckert, D J Pennell, D N Firmin.   

Abstract

The assessment of regional myocardial perfusion during the first-pass of a contrast agent bolus requires tracking of the signal time course for each myocardial segment so that a detailed perfusion map can be derived. To obtain such a map in practice, however, is not trivial because deformation of the shape of the myocardium and respiratory-induced motion render a major difficulty in this process. This study describes an automated approach for motion and deformation tracking of functional myocardial perfusion images. The effectiveness of the described method has been evaluated using a numerical phantom and results are compared with those from existing techniques which use deformable models. Preliminary results from applying our approach to 20 patients are discussed and compared with those from SPECT studies.

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Year:  1998        PMID: 9873904     DOI: 10.1016/s1361-8415(98)80024-8

Source DB:  PubMed          Journal:  Med Image Anal        ISSN: 1361-8415            Impact factor:   8.545


  6 in total

1.  Adaptive and self-evaluating registration method for myocardial perfusion assessment.

Authors:  T Delzescaux; F Frouin; A De Cesare; S Philipp-Foliguet; R Zeboudj; M Janier; A Todd-Pokropek; A Herment
Journal:  MAGMA       Date:  2001-08       Impact factor: 2.310

2.  Color-encoded semiautomatic analysis of multi-slice first-pass magnetic resonance perfusion: comparison to tetrofosmin single photon emission computed tomography perfusion and X-ray angiography.

Authors:  Holger Thiele; Sven Plein; Marcel Breeuwer; John P Ridgway; David Higgins; Penelope J Thorley; Gerhard Schuler; Mohan U Sivananthan
Journal:  Int J Cardiovasc Imaging       Date:  2004-10       Impact factor: 2.357

3.  A quantitative pixel-wise measurement of myocardial blood flow by contrast-enhanced first-pass CMR perfusion imaging: microsphere validation in dogs and feasibility study in humans.

Authors:  Li-Yueh Hsu; Daniel W Groves; Anthony H Aletras; Peter Kellman; Andrew E Arai
Journal:  JACC Cardiovasc Imaging       Date:  2012-02

4.  Automatic postprocessing for the assessment of quantitative human myocardial perfusion using MRI.

Authors:  Andreas Max Weng; Christian Oliver Ritter; Joachim Lotz; Meinrad Joachim Beer; Dietbert Hahn; Herbert Köstler
Journal:  Eur Radiol       Date:  2009-12-17       Impact factor: 5.315

5.  Automated detection of left ventricle in arterial input function images for inline perfusion mapping using deep learning: A study of 15,000 patients.

Authors:  Hui Xue; Ethan Tseng; Kristopher D Knott; Tushar Kotecha; Louise Brown; Sven Plein; Marianna Fontana; James C Moon; Peter Kellman
Journal:  Magn Reson Med       Date:  2020-05-07       Impact factor: 3.737

6.  Automatic in-line quantitative myocardial perfusion mapping: Processing algorithm and implementation.

Authors:  Hui Xue; Louise A E Brown; Sonia Nielles-Vallespin; Sven Plein; Peter Kellman
Journal:  Magn Reson Med       Date:  2019-08-23       Impact factor: 4.668

  6 in total

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