Knowledge of the exact spatial distribution of brain tissues in images acquired by magnetic resonance imaging (MRI) is necessary to measure and compare the performance of segmentation algorithms. Currently available physical phantoms do not satisfy this requirement. State-of-the-art digital brain phantoms also fall short because they do not handle separately anatomical structures (e.g. basal ganglia) and provide relatively rough simulations of tissuefine structure and inhomogeneity. We present a software procedure for the construction of a realistic MRI digital brain phantom. The phantom consists of hydrogen nuclear magnetic resonance spin-lattice relaxation rate (R1), spin-spin relaxation rate (R2), and proton density (PD) values for a 24×...
We introduce a system that automatically segments and classifies features in brain MRIs. It takes 22...
Analysis of brain tissues such as white matter (WM), gray matter (GM), cerebrospinal fluid (CSF), an...
We describe a fully automated method for model-based tissue classification of magnetic resonance (MR...
Knowledge of the exact spatial distribution of brain tissues in images acquired by magnetic resonanc...
Simulations provide a way of generating data where ground truth is known, enabling quantitative test...
International audienceThis paper presents a new technique for assessing the accuracy of segmentation...
PURPOSE: To create a realistic in silico head phantom for the second QSM reconstruction challenge an...
The increased use of computer-aided image analysis techniques, in medical imaging has lead to a grea...
Background: In Multiple Sclerosis, quantification of the volume of brain structures in images acquir...
journal articleObtaining validation data and comparison metrics for segmentation of magnetic resonan...
Obtaining validation data and comparison metrics for segmentation of magnetic resonance images (MRI)...
Accurate brain tissue segmentation of MR (Magnetic Resonance) images has been one of the most import...
Computer simulation and modelling of the human body and its behaviour are very useful tools in situa...
We demonstrate that simulated MR images obtained from Brainweb do not model the partial volume effec...
Magnetic resonance (MR) is a noninvasive imaging modality that has been widely used to image the hum...
We introduce a system that automatically segments and classifies features in brain MRIs. It takes 22...
Analysis of brain tissues such as white matter (WM), gray matter (GM), cerebrospinal fluid (CSF), an...
We describe a fully automated method for model-based tissue classification of magnetic resonance (MR...
Knowledge of the exact spatial distribution of brain tissues in images acquired by magnetic resonanc...
Simulations provide a way of generating data where ground truth is known, enabling quantitative test...
International audienceThis paper presents a new technique for assessing the accuracy of segmentation...
PURPOSE: To create a realistic in silico head phantom for the second QSM reconstruction challenge an...
The increased use of computer-aided image analysis techniques, in medical imaging has lead to a grea...
Background: In Multiple Sclerosis, quantification of the volume of brain structures in images acquir...
journal articleObtaining validation data and comparison metrics for segmentation of magnetic resonan...
Obtaining validation data and comparison metrics for segmentation of magnetic resonance images (MRI)...
Accurate brain tissue segmentation of MR (Magnetic Resonance) images has been one of the most import...
Computer simulation and modelling of the human body and its behaviour are very useful tools in situa...
We demonstrate that simulated MR images obtained from Brainweb do not model the partial volume effec...
Magnetic resonance (MR) is a noninvasive imaging modality that has been widely used to image the hum...
We introduce a system that automatically segments and classifies features in brain MRIs. It takes 22...
Analysis of brain tissues such as white matter (WM), gray matter (GM), cerebrospinal fluid (CSF), an...
We describe a fully automated method for model-based tissue classification of magnetic resonance (MR...