The VTK Journal is an Open Access on-line publication covering the domain of scientific visualization.

The unique characteristics of the VTK Journal include:

-Open-access to articles and reviews
-Open peer-review that invites discussion between reviewers and authors
-Support for continuous revision of articles, code, and reviews

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An Open-Source Solution for Interactive Acquisition, Processing and Transfer of Interventional Ultrasound Images
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Ultrasound has become a very important modality in image-guided therapy. At present, however, the collection, synchronization and transfer of ultrasonic images are more cumbersome than necessary. This paper presents a reusable solution to these problems. We [...]

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Published in The MIDAS Journal

Automatic MS Lesion Segmentation by Outlier Detection and Information Theoretic Region Partitioning
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Multiple Sclerosis (MS) is a neurodegenerative disease that is associated with brain tissue damage primarily observed as white matter abnormalities such as lesions. We present a novel, fully automatic segmentation method for MS lesions in brain MRI that [...]

Software Architecture of a System for Robotic Surgery
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At the German Heart Center Munich we have installed and evaluated a novel system for robotic surgery. Its main features are the incorporation of haptics (by means of strain gauge sensors at the instruments) and partial automation of surgical tasks. [...]

Liver Tumor Segmentation Using Implicit Surface Evolution
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A method for automatic liver tumor segmentation from computer tomography (CT) images is presented in this paper. Segmentation is an important operation before surgery planning, and automatic methods offer an alternative to laborious manual segmentation. In [...]

Interactive Liver Tumor Segmentation Using Graph-cuts and Watershed
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We present in this paper an application of minimal surfaces and Markov random fields to the segmentation of liver tumors. The originality of the work consists in applying these models to the region adjacency graph of a watershed transform. We detail [...]

An Automatic Segmentation of T2-FLAIR Multiple Sclerosis Lesions
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Multiple sclerosis diagnosis and patient follow-up can be helped by an evaluation of the lesion load in MRI sequences. A lot of automatic methods to segment these lesions are available in the literature. The MICCAI workshop Multiple Sclerosis (MS) lesion [...]

MS Lesion Segmentation based on Hidden Markov Chains
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In this paper, we present a new automatic robust algorithm to segment multimodal brain MR images with Multiple Sclerosis (MS) lesions. The method performs tissue classification using a Hidden Markov Chain (HMC) model and detects MS lesions as outliers to the [...]

Liver Tumor segmentation in CT images using probabilistic
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Liver tumors segmentation is an important prerequisite for planning of surgical interventions. For clinical applicability, the segmentation approach must be able to cope with the high variation in shape and gray-value appearance of the liver. We present a [...]

A robust Expectation-Maximization algorithm for Multiple Sclerosis lesion segmentation
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A fully automatic workflow for Multiple Sclerosis (MS) lesion segmentation is described. Fully automatic means that no user interaction is performed in any of the steps and that all parameters are fixed for all the images processed in beforehand. Our workflow [...]

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Publication of the Month
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Diffeomorphic Demons Using ITK's Finite Difference Solver Hierarchy
by Vercauteren T., Pennec X., Perchant A., Ayache N.

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ISSN 2328-3459
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