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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Automatic Mandible Segmentation on CT Images Using Prior Anatomical Knowledge
No opinion
We present a fully automatic method for segmenting mandible in CT images using anatomic landmarks and prior knowledge. The aim is to utilize spatial relationship of anatomic landmarks with image processing techniques to detect mandible robustly and [...]

Automatic Segmentation of Structures in CT Head and Neck Images using a Coupled Shape Model
No opinion
The common approach to do a fully automatic segmentation of multiple structures is an atlas or multi-atlas based solution. These already have proven to be suitable for the segmentation of structures in the head and neck area and provide very accurate [...]

A Multi-atlas Approach for the Automatic Segmentation of Multiple Structures in Head and Neck CT Images
No opinion
A multi-atlas approach is proposed for the automatic segmentation of nine different structures in a set of head and neck CT images for radiotherapy. The approach takes advantage of a training dataset of 25 images to build average head and neck atlases of [...]

Head and Neck Auto Segmentation Challenge based on Non-Local Generative Models
No opinion
We have presented a novel patch label fusion method based on a generative probabilistic approach for weighting the label votes of the neighborhood patches. Additionally a 3D sliding Gaussian window is used to combine the multiples estimations of the [...]

Head and Neck Auto Segmentation Challenge based on Non-Local Generative Models
No opinion
We have presented a novel patch label fusion method based on generative probabilistic approach for weighting the label votes of the neighborhood patches, additionally a 3D sliding Gaussian window is used to combine the multiples estimations of the [...]

Fully Automatic Segmentation of Head and Neck Organs using Active Appearance Models
No opinion
We present a fully automatic model based system for segmenting the mandible, parotid and submandibular glands, brainstem, optic nerves and the optic chiasm in CT images, which won the MICCAI 2015 Head and Neck Auto Segmentation Grand Challenge. The method is [...]

Multi Atlas Segmentation with Active Shape Model Refinement for Multi-Organ Segmentation in Head and Neck Cancer Radiotherapy Planning
No opinion
We describe a segmentation method that was used in the Head and Neck Auto Segmentation Challenge held at the MICCAI 2015 conference. The algorithm consists of two building blocks. First, we employ a multi-atlas segmentation to obtain an initial segmentation [...]

Tensor Spectral Matching of Diffusion Weighted Images
No opinion
Very preterm birth coincides with a period of major development in the brain, with striking changes in volume, cortex folding and significant change at the microstructural level. Diffusion MRI is sensitive to motion of water on the scale of microns, allowing [...]

The graph windowed Fourier transform: a tool to quantify the gyrification of the cerebral cortex
No opinion
The Gyrification Index (GI) quantifies the amount of folding of a cortical surface. In this paper, we show the efficiency of spectral analysis to perform such a task, and in particular we explain how the graph windowed Fourier transform can be used as a tool [...]

Transitively Consistent and Unbiased Multi-Image Registration using Numerically Stable Transformation Synchronisation
No opinion
Transitive consistency of pairwise transformations is a desirable property of groupwise image registration procedures. The transformation synchronisation method (Bernard et al., 2015) is able to retrieve transitively consistent pairwise transformations from [...]

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Publication of the Month
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Head and Neck Auto Segmentation Challenge
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Most Recent Reviews
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Review
A Treatment Planning System for the...
by Anonymous on 2012-07-02 12:07:29
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