The MIDAS Journal is an Open Access on-line publication covering different domains from Visualization to Image processing.

The unique characteristics of the MIDAS 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 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 [...]

3D Segmentation In The Clinic: A Grand Challenge II at MICCAI 2008 - MS Lesion Segmentation
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This document examines the application of a new parametric method on the segmentation of MS lesions in brain sMRI, as applied to the data provided for the MS Lesion Segmentation Challenge at MICCAI 2008. The method uses the vector image joint histogram, [...]

Multiple Sclerosis Lesion Segmentation Using Statistical and Topological Atlases
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This paper presents a new fully automatic method for segmentation of brain images that possess multiple sclerosis (MS) lesions. Multichannel magnetic resonance images are used to delineate multiple sclerosis lesions while segmenting the brain into its [...]

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 [...]

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 [...]

Automatic Segmentation of MS Lesions Using a Contextual Model for the MICCAI Grand Challenge
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Automatically segmenting subcortical structures in brain images has the potential to greatly accelerate drug trials and population studies of disease. Here we propose an automatic subcortical segmentation algorithm using the auto context model. Unlike many [...]

Multiple Sclerosis Detection in Multispectral Magnetic Resonance Images with Principal Components Analysis.
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This paper presents a local feature vector based method for automated Multiple Sclerosis (MS) lesion segmentation of multi spectral MRI data. Twenty datasets from MS patients with FLAIR, T1,T2, MD and FA data with expert annotations are available as training [...]

Helper classes for the BSplineDeformableTransform
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noindent This document describes two new classes that facilitate the use of the doxygen{BSplineDeformableTransform} in multiresolution registration algorithms. The first class, doxygen{GridScheduleComputer}, defines the B-spline grid, based on a [...]

Automatic Coronary Tree Modeling
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In this paper, we present an automatic method for extracting center axis representations (centerlines) of coronary arteries in contrast enhanced (CE)-CT angiography scans. The algorithm first detects the aorta which is used as an initial mask for [...]

Coronary Centerline Extraction Using Multiple Hypothesis Tracking and Minimal Paths
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This paper describes an interactive approach to the identification of coronary arteries in 3D angiography images. The approach is based on a novel multiple hypothesis tracking methodology which is complemented with a standard minimal path search, and it [...]

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Publication of the Month
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Scalable Simple Linear Iterative Clustering (SSLIC) Using a Generic and Parallel Approach
by Lowekamp B., Chen D., Yaniv Z., Yoo T.

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Most Recent Reviews
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Worked very well and was easy to build
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