Cardiac motion estimation using multi-scale feature points
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/1371
Heart illnesses influence the functioning of the cardiac muscle and are the major causes of death in
the world. Optic flow methods are essential tools to assess and quantify the contraction of the cardiac
walls, but are hampered by the aperture problem. Harmonic phase (HARP) techniques measure the
phase in magnetic resonance (MR) tagged images. Due to the regular geometry, patterns generated by
a combination of HARPs and sine HARPs represent a suitable framework to extract landmark features.
In this paper we introduce a new aperture-problem free method to study the cardiac motion by tracking
multi-scale features such as maxima, minima, saddles and corners, on HARP and sine HARP tagged
images.

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plus Cardiac motion estimation using multi-scale feature points by Anonymous on 07-03-2008 for revision #1
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Categories: Blurring filters, Data, Data Representation, Derivatives and Integrals, DICOM, Edge Detection, Error Estimation, Feature extraction, Filtering, Generic Programming, Higher order derivatives, Hypothesis Testing, Image, Images, Information Theory, Linear Algebra, Mathematics, Mesh, Optimization, Path, PointSet, Programming, Segmentation, Spatial Objects
Keywords: Optic Flow, Cardiac Motion Analysis, Scale-Space
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