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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Improvements in SlicerRT, the radiation therapy research toolkit for 3D Slicer
No opinion
Purpose: Recent years have seen growing interest in adaptive radiation therapy (RT), but the existing software tools are not ideal for research use, as they are either expensive and closed proprietary applications or free open-source packages with limited [...]

Gauss-Newton Method for Segmentation assisted Deformable Registration
No opinion
In this work, we try to develop a fast converging method for segmentation assisted deformable registration. The segmentation step consists of a piece-wise constant Mumford-Shah energy model while reg- istration is driven by the sum of squared distances of [...]

Visualization of 4D-PET/CT, Target Volumes and Dose Distribution: Applications in Radiotherapy Planning
No opinion
In radiation treatment (RT) planning medical doctors need to consider a variety of information sources for anatomical and functional target volume delineation. The validation and inspection of the defined target volumes and the resulting RT plan is a complex [...]

Automatic accuracy measurement for multi-modal rigid registration using feature descriptors
No opinion
In radiotherapy (RT) for tumor delineation and diagnostics, complementary information of multi-modal images is used. Using high ionizing radiation, the accuracy of registered volume data is crucial; therefore a reliable and robust evaluation method for [...]

Model-based left ventricle segmentation in 3D ultrasound using phase image
No opinion
In this paper, we propose a semi-automatic method for left ventricle segmentation. The proposed method utilizes a multi-scale quadrature filter method to enhance the 3D volume, followed by a model-based level set method to segment the endocardial surface of [...]

Segmentation of Multi-Center 3D Left Ventricular Echocardiograms by Active Appearance Models
No opinion
Segmentation of 3D echocardiograms (3DEs) is still a challenging task due to the low signal-to-noise ratio, the limited field of view, and typical ultrasound artifacts. We propose to segment the left ventricular endocardial surface by using Active Appearance [...]

Real-time Tracking of the Left Ventricle in 3D Ultrasound Using Kalman Filter and Mean Value Coordinates
No opinion
A method for real-time automatic tracking of the left ventricle (LV) in 3D ultrasound is presented. A mesh model of the LV is deformed using mean value coordinates enabling large variations. Kalman filtering and edge detection is used to track the mesh in [...]

Learning Shape Representations for Multi-Atlas Endocardium Segmentation in 3D Echo Images
No opinion
As part of the CETUS challenge, we present a multi-atlas segmentation framework to delineate the left-ventricle endocardium in echocardiographic images. To increase the robustness of the registration step, we introduce a speckle reduction step and a new shape [...]

Left Ventricle Segmentation in Cardiac Ultrasound Using Hough-Forests With Implicit Shape and Appearance Priors
No opinion
We propose a learning based approach to perform automatic segmentation of the left ventricle in 3D cardiac ultrasound images. The segmentation contour is estimated through the use of a variant of Hough forests whose object localization capabilities are [...]

Endocardial 3D Ultrasound Segmentation using Autocontext Random Forests
No opinion
In this paper, we present the use of a generic image segmentation method, namely a succession of Random Forest classifiers in an autocontext framework, for the MICCAI 2014 Challenge on Endocardial 3D Ultrasound Segmentation (CETUS). The proposed method [...]

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Publication of the Month
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ITK-based Registration of Large Images from Light Microscopy: A Biomedical Application
by Mosaliganti K., Pan T., Machiraju R., Huang K., Saltz J.

Issues Accepting Submissions
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Computational Algorithms
1047 days
Medical Imaging and Computing
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