Dataset Information

Fusion of color Doppler and magnetic resonance images of the heart.

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).

SUBMITTER: Wang C

PROVIDER: S-EPMC3212677 | biostudies-literature | 2011 Dec

REPOSITORIES: biostudies-literature

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Fusion of color Doppler and magnetic resonance images of the heart.

Wang Chao C Chen Ming M Zhao Jiang-Min JM Liu Yi Y

Journal of digital imaging 20111201 6

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. ...[more]

PMID: 21656081

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Project description:Quantitative analysis of craniofacial morphology is of interest to scholars working in a wide variety of disciplines, such as anthropology, developmental biology, and medicine. T1-weighted (anatomical) magnetic resonance images (MRI) provide excellent contrast between soft tissues. Given its three-dimensional nature, MRI represents an ideal imaging modality for the analysis of craniofacial structure in living individuals. Here we describe how T1-weighted MR images, acquired to examine brain anatomy, can also be used to analyze facial features. Using a sample of typically developing adolescents from the Saguenay Youth Study (N?=?597; 292 male, 305 female, ages: 12 to 18 years), we quantified inter-individual variations in craniofacial structure in two ways. First, we adapted existing nonlinear registration-based morphological techniques to generate iteratively a group-wise population average of craniofacial features. The nonlinear transformations were used to map the craniofacial structure of each individual to the population average. Using voxel-wise measures of expansion and contraction, we then examined the effects of sex and age on inter-individual variations in facial features. Second, we employed a landmark-based approach to quantify variations in face surfaces. This approach involves: (a) placing 56 landmarks (forehead, nose, lips, jaw-line, cheekbones, and eyes) on a surface representation of the MRI-based group average; (b) warping the landmarks to the individual faces using the inverse nonlinear transformation estimated for each person; and (3) using a principal components analysis (PCA) of the warped landmarks to identify facial features (i.e. clusters of landmarks) that vary in our sample in a correlated fashion. As with the voxel-wise analysis of the deformation fields, we examined the effects of sex and age on the PCA-derived spatial relationships between facial features. Both methods demonstrated significant sexual dimorphism in craniofacial structure in areas such as the chin, mandible, lips, and nose.

Dataset Information

Fusion of color Doppler and magnetic resonance images of the heart.

Publications

Fusion of color Doppler and magnetic resonance images of the heart.

Similar Datasets

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