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TAG SEPARATION IN CARDIAC TAGGED MRI J. HUANG MICCAI 2008

TAG SEPARATION IN CARDIAC TAGGED MRI J. HUANG MICCAI 2008. Presenter: Lin Zhong. MRI. Magnetic resonance imaging(MRI) primarily a noninvasive medical imaging technique used in radiology to visualize detailed internal structure and limited function of the body

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TAG SEPARATION IN CARDIAC TAGGED MRI J. HUANG MICCAI 2008

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  1. TAG SEPARATION IN CARDIAC TAGGED MRIJ. HUANGMICCAI 2008 Presenter: Lin Zhong

  2. MRI • Magnetic resonance imaging(MRI) • primarily a noninvasive medical imaging technique used in radiology to visualize detailed internal structure and limited function of the body • MRI provides much greater contrast between the different soft tissues of the body than computed tomography (CT) 

  3. Tagged MRI • Tagging consists in tattooing the myocardium with a geometrical pattern (lines or grid), using selective spatial pulses. • the magnetization of the myocardial (or any other) tissue will persist for times (e.g. one cardiac circle) and will create a visible mark in the MR images that moves precisely with the underlying tissue. • can noninvasively render visible the internal motions of tissues. • Pose great challenges to the cardiac image processing

  4. Related work • Morphological operations [Guttman 1994] • Fill in the region between removed tagging lines • Bad generalization • Band pass [osman 1999] • Enhance tag pattern region and increase contrast • Performance depend on the designed filters.

  5. Related work • Band stop [Qian,Z. 2007] • Images are processed in the spectral domain • Low frequency peak at the origin is from actual tissue • Other energy peaks are introduced by tag patterns • Abandon all frequency in the localized regions will cause some artifacts in the recovered images after tag removal

  6. Motivation • The tag patterns have a regular texture • Discrete Cosine Transform (DCT) • The Cardiac images without tag patterns are piecewise smooth with sparse gradients • Wavelet Transform (WT) • Two dictionaries can be built. Tag pattern and piecewise smooth image can be represented sparsely by these two dictionaries. • Tag-only image can be used for tag tracking, the remaining image can be used for accurately localizing the cardiac boundaries.

  7. Problem Formulation • I = S + T • I : tagged cardiac MR image • S: piecewise smooth cardiac image without tags • T: tag-only image

  8. Problems to be solved • Build dictionary A for cardiac images S • Undecimated Wavelet Transforms (UWT) • Suitable for the sparse representation of natural scene • Build dictionary B for tag pattern T • Discrete Cosine Transform (DCT) • Deal images in the frequency domain, and is appropriate for a sparse representation of periodic or smooth behaviors. • Find optimal coefficients for Image decomposition via the combination of sparse representations and a variational approach. ITIP, 2005

  9. Optimization of Coefficients • Original Objective function • Modified objective function • TV penalty guide S to be a piece wise smooth image with sparse gradient. • Block-coordinate Relaxation algorithm[Bruce,1998]

  10. Results

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