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» Two Methods for Validating Brain Tissue Classifiers
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ICCV
2007
IEEE
14 years 7 months ago
3D Variational Brain Tumor Segmentation using a High Dimensional Feature Set
Tumor segmentation from MRI data is an important but time consuming task performed manually by medical experts. Automating this process is challenging due to the high diversity in...
Albert Murtha, Dana Cobzas, Mark Schmidt, Martin J...
MICCAI
2005
Springer
14 years 6 months ago
Synthetic Ground Truth for Validation of Brain Tumor MRI Segmentation
Validation and method of comparison for segmentation of magnetic resonance images (MRI) presenting pathology is a challenging task due to the lack of reliable ground truth. We prop...
Marcel Prastawa, Elizabeth Bullitt, Guido Gerig
DAGM
2008
Springer
13 years 7 months ago
Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification
Three-dimensional electron-microscopic image stacks with almost isotropic resolution allow, for the first time, to determine the complete connection matrix of parts of the brain. I...
Björn Andres, Ullrich Köthe, Moritz Helm...
PAMI
2010
122views more  PAMI 2010»
13 years 3 months ago
Domain Adaptation Problems: A DASVM Classification Technique and a Circular Validation Strategy
—This paper addresses pattern classification in the framework of domain adaptation by considering methods that solve problems in which training data are assumed to be available o...
Lorenzo Bruzzone, Mattia Marconcini
MICCAI
2008
Springer
14 years 6 months ago
A Discriminative Model-Constrained Graph Cuts Approach to Fully Automated Pediatric Brain Tumor Segmentation in 3-D MRI
In this paper we present a fully automated approach to the segmentation of pediatric brain tumors in multi-spectral 3-D magnetic resonance images. It is a top-down segmentation app...
Michael Wels, Gustavo Carneiro, Alexander Aplas,...