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Multi-Atlas-based Segmentation with Hierarchical Max-Flow
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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 [...]

3D Segmentation in the Clinic: A Grand  Challenge II: MS lesion segmentation
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This paper describes the setup of a segmentation competition for the automatic extraction of Multiple Sclerosis (MS) lesions from brain Magnetic Resonance Imaging (MRI) data. This competition is one of three competitions that make up a comparison workshop at [...]

Automated Brain-Tissue Segmentation by Multi-Feature SVM Classification
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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 [...]

MR Brain Segmentation using Decision Trees
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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 [...]

Gaussian Intensity Model with Neighborhood Cues for Fluid-Tissue Categorization of Multi-Sequence MR Brain Images
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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 [...]

Automatic Brain Tissue Segmentation of Multi-sequence MR Images Using Random Decision Forests
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This work is integrated in the MICCAI Grand Challenge: MR Brain Image Segmentation 2013. It aims for the automatic segmentation of brain into Cerebrospinal fluid (CSF), Gray matter (GM) and White matter (WM). The provided dataset contains patients with white [...]

Semi-automated cardiac segmentation on cine magnetic  resonance images using GVF-Snake deformable models
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The segmentation of left ventricular structures is necessary for the evaluation of the ejection fraction (EF) and the myocardial mass (LVM). A semi-automated 2D algorithm using connected filters and a deformable model allowing an accurate endocardial [...]

Evaluation Framework for Algorithms Segmenting Short Axis Cardiac MRI.
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The motivation of the segmentation challenge is to quantitatively analyze global and regional cardiac function from cine magnetic resonance (MR) images, clinical parameters such as ejection fraction (EF), left ventricle myocardium mass (MM), and stroke volume [...]

A nonparametric, entropy-minimizing MRI tissue classification algorithm implementation using ITK
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This paper focuses on the role of open-source software in the development of a novel magnetic resonance image (MRI) tissue classification algorithm. Specifically, we describe the of use existing classes in the Insight Segmentation and Registration Toolkit [...]

LV Challenge LKEB Contribution: Fully Automated Myocardial Contour Detection
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In this paper a contour detection method is described and evaluated on the evaluation data sets of the Cardiac MR Left Ventricle Segmentation Challenge as part of MICCAI 2009’s 3D Segmentation Challenge for Clinical Applications. The proposed method, using [...]

Pseudo-CT generation from multiple MR images for small animal irradiation
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Introduction. Computed tomography (CT) is the standard imaging modality for radiation therapy treatment planning (RTTP) because of its ability to provide information on electron density. However, magnetic resonance (MR) imaging provides superior soft tissue [...]

Knowledge-Based Segmentation of Brain MRI Scans Using the Insight Toolkit
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An Insight Toolkit (ITK) implementation of our knowledgebased segmentation algorithm applied to brain MRI scans is presented in this paper. Our algorithm is a refinement of the work of Teo, Saprio, and Wandall. The basic idea is to incorporate prior [...]

New Expectation Maximization Segmentation Pipeline in Slicer 3
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Many neuroanatomy studies rely on brain tissue segmentation in Magnetic Resonance images (MRI). The Expectation-Maximization (EM) theory offers a popular framework for this task. We studied the EM algorithm developed at the Surgical Planning Laboratory (SPL) [...]

Cardiac Motion Recovery by Coupling an Electromechanical Model and Cine-MRI Data: First Steps
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We present a framework for cardiac motion recovery using the adjustment of an electromechanical model of the heart to cine Magnetic Resonance Images (MRI). This approach is based on a constrained minimisation of an energy coupling the model and the data. Our [...]


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