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Tensor Spectral Matching of Diffusion Weighted Images
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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 [...]

A Skull-Stripping Filter for ITK
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Skull-stripping (or brain extraction) is an important pre-processing step in neuroimage analysis. This document describes a skull-stripping filter implemented using the Insight Toolkit ITK, which we named itk::StripTsImageFilter. It is a composite filter [...]

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 [...]

EM Segmentation: Automatic Tissue Class Intensity Initialization Using K-means
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ABSTRACT Brain tissue segmentation is important in many medical image applications. We augmented the Expectation-Maximization segmentation algorithm in Slicer3 (www.spl.harvard.edu) . Currently, in the EM Segmenter module in Slicer3 user input is necessary to [...]

Modified Expectation Maximization Method for Automatic Segmentation of MR Brain Images
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An automated method of MR Brain image segmentation is presented. A block based Expectation Maximization method is presented for the tissue classification of MR Brain images. The standard Gaussian Mixture Model is the most widely used method for MR Brain Image [...]

Multimodal MR Brain Segmentation Using Bayesian-based Adaptive Mean-Shift (BAMS)
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In this paper, we validate our proposed segmentation algorithm called Bayesian-based adaptive mean-shift (BAMS) on real mul-timodal MR images provided by the MRBrainS challenge. BAMS is a fully automatic unsupervised segmentation algorithm. It is based on the [...]

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 [...]

Conformal Flattening ITK Filter
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This paper describes the Insight Toolkit (ITK) Conformal Flattening filter: itkConformalFlatteningFilter. This ITK filter is an implementation of a paper by Sigurd Angenent, et al., “On the Laplace-Beltrami Operator and Brain Surface Flattening”. This [...]

Coupling Finite Element and Mesh-free Methods for Modelling Brain Deformation in Response to Tumour Growth
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Very little is known about the deformation effects of tumour growth within the brain. Computer simulations have the potential to calculate such deformations. A method for computing localised high deformations within the brain's soft tissue is presented. [...]

Realistic And Efficient Brain-Skull Interaction Model For Brain Shift Computation
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In this paper we propose the usage of a very efficient contact implementation for modeling the brain-skull interaction. This contact algorithm is specially design for our Dynamic Relaxation solution method for solving soft-tissue registration problems. It [...]

Automatic MS Lesion Segmentation by Outlier Detection and Information Theoretic Region Partitioning
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Multiple Sclerosis (MS) is a neurodegenerative disease that is associated with brain tissue damage primarily observed as white matter abnormalities such as lesions. We present a novel, fully automatic segmentation method for MS lesions in brain MRI that [...]

Automated MS-Lesion Segmentation by K-Nearest Neighbor Classification
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This paper proposes a new method for fully automated multiple sclerosis (MS) lesion segmentation in cranial magnetic resonance (MR) imaging. The algorithm uses the T1-weighted and the fluid attenuation inversion recovery scans. It is based the K-Nearest [...]

Multimodal Analysis of Vasogenic Edema in Glioblastoma Patients for Radiotherapy Planning
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Glioblastoma (GBM) is the most common type of primary brain tumor, which is characterized by an infiltrative growth pattern. In current practice, radiotherapy planning is primarily based upon T2 FLAIR MRI despite its known lack of specificity in the detection [...]

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 [...]

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 [...]

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 [...]

Atlas to Image-with-Tumor Registration Based on Demons and Deformation Inpainting
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This paper presents a method for nonlinear registration of images, where there exists no one-to-one correspondence in parts of the image. Such a situation occurs for instance in the case where an atlas of normal anatomy shall be matched to pathological data, [...]

MAP–Based Framework for Segmentation of MR Brain Images Based on Visual Appearance and Prior Shape
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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 [...]

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 [...]

Fully automatic brain segmentation using model-guided level sets and skeleton-based models
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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 [...]

Open Topology: A Toolkit for Brain Isosurface Correction
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Isosurface extraction from brain images often creates handles between brain folds that are anatomically separated. Although manual editing could optimally correct these anatomical errors, it is not realistic due the size of the 3D data and the convoluted [...]

Framework for the Statistical Shape Analysis of Brain Structures using SPHARM-PDM
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Shape analysis has become of increasing interest to the neuroimaging community due to its potential to precisely locate morphological changes between healthy and pathological structures. This manuscript presents a comprehensive set of tools for the [...]

Auto-kNN: Brain Tissue Segmentation using Automatically Trained k-Nearest-Neighbor Classification
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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 [...]

Multi-Atlas Brain MRI Segmentation with Multiway Cut
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Characterization of anatomical structure of the brain and effi cient algorithms for automatically analyzing brain MRI have gained an increasing interest in recent years. In this paper, we propose an algorithm that automatically segments the anatomical [...]


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ISSN 2327-770X
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