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 [...]

EM Segmentation: Automatic Tissue Class Intensity Initialization Using K-means
No opinion
ABSTRACT Brain tissue segmentation is important in many medical image applications. We augmented the Expectation-Maximization segmentation algorithm in Slicer3 ( . Currently, in the EM Segmenter module in Slicer3 user input is necessary to [...]

Atlas to Image-with-Tumor Registration Based on Demons and Deformation Inpainting
No opinion
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, [...]

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 [...]

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 [...]

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 [...]

Automated MS-Lesion Segmentation by K-Nearest Neighbor Classification
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
No opinion
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 [...]

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 [...]

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 [...]

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