Medical Image Processing
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Cardiovascular risk assessment: A multi-modal imaging challenge!
Cardiovascular diseases are the main cause of morbidity and mortality in the Western world. Imaging techniques, such as MRI, CT, nuclear imaging and ultrasound, play an increasingly important role in improving the (early) detection, diagnosis, therapy planning, guidance and monitoring of cardiovascular disease, by providing detailed information on patient anatomy, function and pathology. A major scientific challenge is the integrated, quantitative analysis of the complementary information provided by these imaging techniques. We develop and validate advanced quantitative image analysis techniques to optimally exploit the rich information present in these complementary imaging techniques, to improve the overall management of cardiovascular disease. Heart in 3D is a Medical Delta project, supported by Pieken in de Delta (Ministry of Economic Affairs). Contact Lucas van Vliet / Wiro Niessen.
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The quest for biomarkers of neurological disorders using Diffusion Weighted MRI
Diffusion Tensor MRI (DTI) provides information about changes in the brain's white matter, both physiologically (aging) and pathologically (e.g. Alzheimer's disease). DTI measures the ability of water molecules to move freely in the surrounding tissue. Healthy white matter tracts show high diffusion along and low diffusion across axons. Such anisotropy is measured by DTI. Although pathology is generally characterized by increased isotropy, it is not easily recognized especially due to the lack of a reference. Our research focuses on identifying deviating structures in DTI data by developing methods that (i) improve tract characterization by explicitly modeling crossing tracts; (ii) establish both spatial and temporal registration; (iii) statistically model changes in white matter structure; (iv) identify spatiotemporal biomarkers that characterize disease. Exemplary movies: http://www.qi.tnw.tudelft.nl/~frans/movies/Tractography.avi
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Virtual colonoscopy: electronic cleansing and Computer Aided Detection of polyps
Virtual colonoscopy is a non-invasive method to screen for polyps - the precursors of colon cancer - based on 3D CT images. Since fecal remains may mimic or obscure polyps, the technique is improved by adding an oral contrast agent to the patient's diet. However, inhomogeneous mixing of contrast and fecal material complicates the interpretation of the images. We are developing sophisticated methods for electronic cleansing, i.e. image processing algorithms to automatically segment the colon surface from the CT data, prior to visualization. To assist the radiologist in this time consuming screening task, we are also developing a Computer Aided Detection systems for finding polyps. Examplary movies:
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