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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Automated Brain-Tissue Segmentation by Multi-Feature SVM Classification
No opinion
We present a method for automated brain-tissue segmentation through voxelwise classification. Our algorithm uses manually labeled training images to train a support vector machine (SVM) classifier, which is then used for the segmentation of target images. The [...]

Gaussian Intensity Model with Neighborhood Cues for Fluid-Tissue Categorization of Multi-Sequence MR Brain Images
No opinion
This work presents an automatic brain MRI segmentation method which can classify brain voxels into one of three main tissue types: gray matter (GM), white matter (WM) and Cerebro-spinal Fluid (CSF). Intensity-model based classification of MR images has proven [...]

MR Brain Segmentation using Decision Trees
No opinion
Segmentation of the human cerebrum from magnetic resonance images (MRI) into its component tissues has been a defining problem in medical imaging. Until recently, this has been solved as the tissue classification of the T1-weighted (T1-w) MRI, with numerous [...]

MAP–Based Framework for Segmentation of MR Brain Images Based on Visual Appearance and Prior Shape
No opinion
We propose a new MAP-based technique for the unsupervised segmentation of different brain structures (white matter, gray matter, etc.) from T1-weighted MR brain images. In this paper, we follow a procedure like most conventional approaches, in which [...]

Fully automatic brain segmentation using model-guided level sets and skeleton-based models
No opinion
A fully automatic brain segmentation method is presented. First the skull is stripped using a model-based level set on T1-weighted inversion recovery images, then the brain ventricles and basal ganglia are segmented using the same method on T1-weighted [...]

Multi-Atlas-based Segmentation with Hierarchical Max-Flow
No opinion
This study investigates a method for brain tissue segmentation from 3D T1 weighted (T1w) MR images via convex relaxation with a hierarchical ordering constraint. It employs a multi-atlas-based initialization from 5 training images and is tested on 12 T1w MR [...]

Automated Walks using Machine Learning for Segmentation
No opinion
This paper describes an automated algorithm for segmentation of brain structures (CSF, white matter, and gray matter) in MR images. We employ machine learning, i.e. k-Nearest Neighbors, of features derived from k-means, Canny edge detection, and Tourist [...]

Auto-kNN: Brain Tissue Segmentation using Automatically Trained k-Nearest-Neighbor Classification
No opinion
In this paper we applied one of our regularly used processing pipelines for fully automated brain tissue segmentation. Brain tissue was segmented in cerebrospinal fluid (CSF), gray matter (GM) and white matter (WM). Our algorithms for skull stripping, tissue [...]

The Image-based Vascular Analysis Toolkit (IvanTk)
No opinion
This document describes the Image-based Vascular Analysis Toolkit (IvanTk), a set of cross-platform C++ open source software libraries for the detection, extraction and modeling of vessels in 2D/3D medical images based on the Insight Toolkit. We provide an [...]

Skull Base Surgery Navigation System Based on Updating Preoperative Images Using Positional Information of Surgical Tools
No opinion
In this paper, we introduce a new concept of surgical navigation which processes information interactively between the real and virtual spaces, namely, updating preoperative images using the positional information of surgical tools. Although the organs are [...]

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

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