Cardiac MR image processing

I am currently developing processing and visualisation tools to improve cardiac MR including: cardiac diffusion tensor imaging, cardiac myocyte tractography, and multi-modality image registration.

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Things I am working on

Cardiac MR: diffusion tensor imaging

Cardiac diffusion analysis tool

Analysis software tool developed in MATLAB. It outputs multiple DTI maps including: fractional anisotropy, mean diffusivity, tensor mode,  helical angle and secondary eigenvector orientation in relation to the local cardiac coordinates. The processing includes multiple steps: data quality assessment, in-plane registration of different averages, and segmentation tools.

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Myocyte orientation 3D visualisation

Short-axis plane of the left ventricle showing the mean orientation of the myocyctes for each MR voxel. The cylindrical glyphs are colour-coded according to their helical angle. This data was acquired in vivo and it is shown from different angles.

Myocyte tractography

Left ventricular tractograms of a porcine heart. The tracts are colour coded according to the local helical angle and shown from different angles and different levels of angle threshold. This data was acquired ex vivo.

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Diffusion tensor visulisation

Visualisation of the entire diffusion tensor with superquadric glyphs. This particular set of images show an horizontal long-axis plane of the heart, viewed from different angles. This data was acquired in vivo.

Secondary eigenvector in disease

Short-axis data acquired in vivo in a subject with hypertrophic cardiomyopathy. The secondary eigenvector direction is represented by white cylinders superimposed in the superquadric glyphs showing the entire diffusion tensor. The secondary eigenvectors are in general oriented at low angles to the short-axis plane.

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Publications

- Ferreira, P. F., Kilner, P. J., McGill, L.A., et al. In vivo cardiovascular magnetic resonance diffusion tensor imaging shows evidence of abnormal myocardial laminar orientations and mobility in hypertrophic cardiomyopathy. J Cardiovasc Magn Reson (2014): 87. Winner of the Pohost Prize 2014, for best JCMR paper.

- Scott, A. D., Ferreira, P. F. A. D. C., Nielles-Vallespin, S., et al. Optimal diffusion weighting for in vivo cardiac diffusion tensor imaging. Magn Reson Med (2014).

- Tunnicliffe, E. M., Scott, A. D., Ferreira, P., et al. Intercentre reproducibility of cardiac apparent diffusion coefficient and fractional anisotropy in healthy volunteers. J Cardiovasc Magn Reson (2014): 31.

- Ismail, T. F., Hsu, L.-Y., Greve, A. M., et al. Coronary microvascular ischemia in hypertrophic cardiomyopathy - a pixel-wise quantitative cardiovascular magnetic resonance perfusion study. J Cardiovasc Magn Reson (2014): 49.

- Ferreira, P. F., Gatehouse, P. D., Mohiaddin, R. H., et al. Cardiovascular magnetic resonance artefacts. J Cardiovasc Magn Reson (2013): 41.

- McGill, L.-A., Ismail, T. F., Nielles-Vallespin, S., et al. Reproducibility of in-vivo diffusion tensor cardiovascular magnetic resonance in hypertrophic cardiomyopathy. J Cardiovasc Magn Reson (2012): 86.

- Ferreira, P. F., Gatehouse, P. D., and Firmin, D. N. Myocardial first-pass perfusion imaging with hybrid-EPI: frequency-offsets and potential artefacts. J Cardiovasc Magn Reson (2012): 44.

- Nielles-Vallespin, S., Mekkaoui, C., Gatehouse, P., et al. In vivo diffusion tensor MRI of the human heart: reproducibility of breath-hold and navigator-based approaches. Magn Reson Med (2013): 454-65.

- Ferreira, P., Gatehouse, P., Kellman, P., et al. Variability of myocardial perfusion dark rim Gibbs artifacts due to sub-pixel shifts. J Cardiovasc Magn Reson (2009): 17.

- Ferreira, P., Gatehouse, P., Bucciarelli-Ducci, C., et al. Measurement of myocardial frequency offsets during first pass of a gadolinium-based contrast agent in perfusion studies. Magn Reson Med (2008): 860-70.

- Gerber, B. L., Raman, S. V., Nayak, K., et al. Myocardial first-pass perfusion cardiovascular magnetic resonance: history, theory, and current state of the art. J Cardiovasc Magn Reson (2008): 18.

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