Literature DB >> 20967793

Realistic simulation of cardiac magnetic resonance studies modeling anatomical variability, trabeculae, and papillary muscles.

C Tobon-Gomez1, F M Sukno, B H Bijnens, M Huguet, A F Frangi.   

Abstract

Simulated magnetic resonance imaging brain studies have been generated for over a decade. Despite their useful potential, simulated cardiac studies are only emerging. This article focuses on the realistic simulation of cardiac magnetic resonance imaging datasets. The methodology is based on the XCAT phantom, which is modified to increase realism of the simulated images. Modifications include the modeling of trabeculae and papillary muscles based on clinical measurements and published data. To develop and evaluate our approach, the clinical database included 40 patients for anatomical measurements, 10 patients for papillary muscle modeling, and 10 patients for local gray value statistics. The virtual database consisted of 40 digital voxel phantoms. Histograms from different tissues were obtained from the real datasets and compared with histograms of the simulated datasets with the Chi-square dissimilarity metric (χ(2)) and Kullback-Leibler divergence. For the original phantom, χ(2) values averaged 0.65 ± 0.06 and Kullboek-Leibler values averaged 0.69 ± 0.38. For the modified phantom, χ(2) values averaged 0.34 ± 0.12 and Kullboek-Leibler values averaged 0.32 ± 0.15. The proposed approach demonstrated a noticeable improvement of the local appearance of the simulated images with respect to the ones obtained originally.
© 2010 Wiley-Liss, Inc.

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Year:  2011        PMID: 20967793     DOI: 10.1002/mrm.22621

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  8 in total

Review 1.  Application of the 4-D XCAT Phantoms in Biomedical Imaging and Beyond.

Authors:  W Paul Segars; B M W Tsui; George S K Fung; Ehsan Samei
Journal:  IEEE Trans Med Imaging       Date:  2017-08-10       Impact factor: 10.048

2.  Realistic analytical polyhedral MRI phantoms.

Authors:  Tri M Ngo; George S K Fung; Shuo Han; Min Chen; Jerry L Prince; Benjamin M W Tsui; Elliot R McVeigh; Daniel A Herzka
Journal:  Magn Reson Med       Date:  2015-10-19       Impact factor: 4.668

Review 3.  Cardiac image modelling: Breadth and depth in heart disease.

Authors:  Avan Suinesiaputra; Andrew D McCulloch; Martyn P Nash; Beau Pontre; Alistair A Young
Journal:  Med Image Anal       Date:  2016-06-17       Impact factor: 8.545

4.  MRXCAT: Realistic numerical phantoms for cardiovascular magnetic resonance.

Authors:  Lukas Wissmann; Claudio Santelli; William P Segars; Sebastian Kozerke
Journal:  J Cardiovasc Magn Reson       Date:  2014-08-20       Impact factor: 5.364

5.  Synthetic generation of myocardial blood-oxygen-level-dependent MRI time series via structural sparse decomposition modeling.

Authors:  Cristian Rusu; Rita Morisi; Davide Boschetto; Rohan Dharmakumar; Sotirios A Tsaftaris
Journal:  IEEE Trans Med Imaging       Date:  2014-03-21       Impact factor: 10.048

6.  An Anthropomorphic Digital Reference Object (DRO) for Simulation and Analysis of Breast DCE MRI Techniques.

Authors:  Leah Henze Bancroft; James Holmes; Ryan Bosca-Harasim; Jacob Johnson; Pingni Wang; Frank Korosec; Walter Block; Roberta Strigel
Journal:  Tomography       Date:  2022-04-02

Review 7.  Virtual clinical trials in medical imaging: a review.

Authors:  Ehsan Abadi; William P Segars; Benjamin M W Tsui; Paul E Kinahan; Nick Bottenus; Alejandro F Frangi; Andrew Maidment; Joseph Lo; Ehsan Samei
Journal:  J Med Imaging (Bellingham)       Date:  2020-04-11

8.  Atlas-based analysis of cardiac shape and function: correction of regional shape bias due to imaging protocol for population studies.

Authors:  Pau Medrano-Gracia; Brett R Cowan; David A Bluemke; J Paul Finn; Alan H Kadish; Daniel C Lee; Joao A C Lima; Avan Suinesiaputra; Alistair A Young
Journal:  J Cardiovasc Magn Reson       Date:  2013-09-13       Impact factor: 5.364

  8 in total

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