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This paper describes an automated algorithm for segmentation
of brain structures (CSF, white matter, and gray matter) in MR
images. We employ machine learning, i.e. k-Nearest Neighbors, of features
derived from k-means, Canny edge detection, and Tourist [...]

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

Automated Brain-Tissue Segmentation by Multi-Feature SVM Classification
Published in The MIDAS Journal
Published in The MIDAS Journal
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 [...]

Automatic Brain Tissue Segmentation of Multi-sequence MR Images Using Random Decision Forests
Published in The MIDAS Journal
Published in The MIDAS Journal
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 [...]

Malignant gliomas are highly heterogeneous brain tumors with complex an-
isotropic growth patterns and occult invasion. Computational modeling of cell migration and proliferation has been subject of intensive research aiming at a deeper understanding of the [...]

3D Segmentation in the Clinic: A Grand Challenge II: MS lesion segmentation
Published in The MIDAS Journal
Published in The MIDAS Journal
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 [...]

Multimodal Analysis of Vasogenic Edema in Glioblastoma Patients for Radiotherapy Planning
Published in The MIDAS Journal
Published in The MIDAS Journal
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 [...]

In this document we present the implementation of three fuzzy clustering algorithms using the Insight Toolkit ITK. Firstly, we developed the conventional Fuzzy C-Means that will serve as the basis for the rest of the proposed algorithms. The next algorithms [...]

This document describes the derivation of the mixture models commonly used in the literature to describe the probabilistic nature of speckle: The Gaussian Mixture Model, the Rayleigh Mixture Model, the Gamma Mixture Model and the Generalized Gamma Mixture [...]

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 [...]

Non-negative matrix factorization framework for dimensionality reduction and unsupervised clustering
Published in The Insight Journal
Published in The Insight Journal
Non-negative Matrix Factorization (NMF) is a robust approach to learning spatially localized parts-based subspace patterns in applications such as document analysis, image interpretation, and gene expression analysis. NMF-based decomposition capabilities are [...]

Characterization of anatomical structure of the brain and efficient 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 [...]

Minimally Interactive Knowledge-based Coronary Tracking in CTA using a Minimal Cost Path
Published in The MIDAS Journal
Published in The MIDAS Journal
An algorithm for minimally interactive coronary artery tracking is presented. Tracking ability and accuracy results are demonstrated on 16 images CTA images.
First, a region of interest is automatically selected and a denoising filter applied. Then, for each [...]

An entropy based multi-thresholding method for semi-automatic segmentation of liver tumors
Published in The MIDAS Journal
Published in The MIDAS Journal
Liver cancer is the fifth most commonly diagnosed cancer and the third most common cause of death
from cancer worldwide. A precise analysis of the lesions would help in the staging of the tumor and
in the evaluation of the possible applicable therapies. In [...]
