Titlebook: Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2004; 7th International Co Christian Barillot,David R. Haynor,Pierre H

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0302-9743 ld in Saint-Malo, Brittany, France at the “Palais du Grand Large” conference center, September 26–29, 2004. The p- posaltohostMICCAI2004wasstronglyencouragedandsupportedbyIRISA, Rennes. IRISA is a publicly funded national research laboratory with a sta? of 370,including150full-timeresearchscientists

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Vessel Segmentation Using a Shape Driven Flowddress this problem, we combine image statistics and shape information to derive a region-based active contour that segments tubular structures and penalizes leakages. We present results on synthetic and real 2D and 3D datasets.

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Simultaneous Boundary and Partial Volume Estimation in Medical Imagese classes, as well as the the locations of tissue boundaries within the image. The latter allows the partial volume fractions to be constrained to represent pure or nearly pure tissue except along tissue boundaries. We demonstrate the application of the algorithm on simulated and real magnetic resonance images.

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Local Watershed Operators for Image Segmentationition, we show that this local computation of watershed regions can be used as an operator in other segmentation techniques such as seeded region growing, region competition or markers-based watershed segmentation. We illustrate the efficiency and accuracy of the proposed technique on several MRA and CTA data.

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Adaptive Segmentation of Multi-modal 3D Data Using Robust Level Set Techniquesons. The method can be applied to different kinds of data, e.g for segmenting anatomical structures in 3D magnetic resonance images and angiography. Experimental results of these two types of data are discussed.