Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
Journal of Imaging Informatics in Medicine
Published in: Journal of Digital Imaging 6/2011

Open Access 01-12-2011

Fusion of Color Doppler and Magnetic Resonance Images of the Heart

Authors: Chao Wang, Ming Chen, Jiang-min Zhao, Yi Liu

Published in: Journal of Imaging Informatics in Medicine | Issue 6/2011

Login to get access

Abstract

This study was designed to establish and analyze color Doppler and magnetic resonance fusion images of the heart, an approach for simultaneous testing of cardiac pathological alterations, performance, and hemodynamics. Ten volunteers were tested in this study. The echocardiographic images were produced by Philips IE33 system and the magnetic resonance images were generated from Philips 3.0-T system. The fusion application was implemented on MATLAB platform utilizing image processing technology. The fusion image was generated from the following steps: (1) color Doppler blood flow segmentation, (2) image registration of color Doppler and magnetic resonance imaging, and (3) image fusion of different image types. The fusion images of color Doppler blood flow and magnetic resonance images were implemented by MATLAB programming in our laboratory. Images and videos were displayed and saved as AVI and JPG. The present study shows that the method we have developed can be used to fuse color flow Doppler and magnetic resonance images of the heart. We believe that the method has the potential to: fill in information missing from the ultrasound or MRI alone, show structures outside the field of view of the ultrasound through MR imaging, and obtain complementary information through the fusion of the two imaging methods (structure from MRI and function from ultrasound).
Appendix
Available only for authorised users
Literature
1.
Burri H, Lerch R: Utility of echocardiography for tailoring cardiac resynchronisation therapy. Kardiovaskuläre Medizin 9:188–196, 2006
2.
Cerqueira MD, Weissman NJ, Dilsizian V, et al: Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. Circulation 105:539–542, 2002PubMedCrossRef
3.
Hunt AC, Chow Sl, Escaned J, et al: Evaluation of a theoretical Doppler index to noninvasively estimate peak dP/dt using continuous wave Doppler ultrasound of ascending aortic flow in man. Cathet Cardiovasc Diagn 23:219–222, 1991PubMedCrossRef
4.
Okada M, Imai Y, Kim T, et al: Comparison of enhancement patterns of histologically confirmed hepatocellular carcinoma between gadoxetate- and ferucarbotran-enhanced magnetic resonance imaging. J Magn Reson Imaging 32:903–913, 2010PubMedCrossRef
5.
Cimmino MA, Grassi W: What is new in ultrasound and magnetic resonance imaging for musculoskeletal disorders? Clin Rheumatol 22:1141–1148, 2008
6.
Porter BC, Rubens DJ, Strang JG, et al: Three-dimensional registration and fusion of ultrasound and MRI using major vessels as fiducial markers. IEEE Trans Med Imag 20:354–359, 2001CrossRef
7.
Rajpoot K, Noble JA, Grau V, et al: Multiview RT3D echocardiography image fusion. Functional imaging and modeling of the heart. Lect Note Comput Sci 5528:134–143, 2009CrossRef
8.
Rasche V, Mansour M, Reddy V, et al: Fusion of three-dimensional X-ray angiography and three-dimensional echocardiography. Int J Comput Assist Radiol Surg 2:293–303, 2008CrossRef
9.
Gonzalez RC: Digital image processing using MATLAB. Prentice Hall, London, 2003, pp 134–178
10.
Amin D, Kanade T, DiGioia A, et al: Ultrasound registration of the bone surface for surgical navigation. Comput Aided Surg 8:1–16, 2003PubMedCrossRef
11.
Hata N, Dohi T, Iseki H, et al: Development of a frameless and armless stereotactic neuronavigation system with ultrasonographic registration. Neurosurgery 41:608–614, 1997PubMed
12.
Lindseth F, Kaspersen JH, Ommedal S, et al: Multimodal image fusion in ultrasound-based neuronavigation: improving overview and interpretation by integrating preoperative MRI with intraoperative 3D ultrasound. Comput Aided Surg 8:49–69, 2003PubMedCrossRef
13.
Wein W, Roper B, Navab N: Automatic registration and fusion of ultrasound with CT for radiotherapy. Med Image Comput Comput Assist Interv 8:303–311, 2005PubMed
14.
Fuller DB, Jin H, Koziol JA, et al: CT-ultrasound fusion prostate brachytherapy: a dynamic dosimetry feedback and improvement method. A report of 54 consecutive cases. Brachytherapy 4:207–216, 2005PubMedCrossRef
15.
Julow J: Image fusion guided brachytherapy of brain tumors. Ideggyogy Sz 63:164–169, 2010PubMed
16.
Huo YM, Chen YZ: Research on HIFU technology. Acoust Technol 19:39–45, 2000
17.
Penney G, Blackall J, Hamady M, et al: Registration of freehand 3D ultrasound and magnetic resonance liver images. Med Image Anal 8:81–91, 2004PubMedCrossRef
18.
Jung EM, Schreyer AG, Schacherer D, et al: New real-time image fusion technique for characterization of tumor vascularisation and tumor perfusion of liver tumors with contrast-enhanced ultrasound, spiral CT or MRI: first results. Clin Hemorheol Microcirc 43:57–69, 2009PubMed
Metadata
Title
Fusion of Color Doppler and Magnetic Resonance Images of the Heart
Authors
Chao Wang
Ming Chen
Jiang-min Zhao
Yi Liu
Publication date
01-12-2011
Publisher
Springer-Verlag
Published in
Journal of Imaging Informatics in Medicine / Issue 6/2011
Print ISSN: 2948-2925
Electronic ISSN: 2948-2933
DOI
https://doi.org/10.1007/s10278-011-9393-y

Other articles of this Issue 6/2011

Journal of Digital Imaging 6/2011 Go to the issue

BriefCommunication

Fully Automatic Region of Interest Selection in Glomerular Filtration Rate Estimation from 99mTc-DTPA Renogram

OriginalPaper

X-ray Image Classification Using Random Forests with Local Wavelet-Based CS-Local Binary Patterns

OriginalPaper

Evaluation of Novel Genetic Algorithm Generated Schemes for Positron Emission Tomography (PET)/Magnetic Resonance Imaging (MRI) Image Fusion

BriefCommunication

DRR and Portal Image Registration for Automatic Patient Positioning in Radiotherapy Treatment

OriginalPaper

Computerized Analysis of Pneumoconiosis in Digital Chest Radiography: Effect of Artificial Neural Network Trained with Power Spectra

BriefCommunication

Use of a Rich Internet Application Solution to Present Medical Images