Add to ORKGThrough this work we propose a computational techniquefor the segmentation of a brain tumor, identified as meningioma(MGT), which is present in magnetic resonance images(MRI). This technique consists of 3 stages developed inthe three-dimensional domain: pre-processing, segmentationand post-processing. The percent relative error (PrE) is consideredto compare the segmentations of the MGT, generatedby a neuro-oncologist manually, with the dilated segmentationsof the MGT, obtained automatically. The combination ofparameters linked to the lowest PrE, provides the optimal parametersof each computational algorithm that makes up theproposed computational technique. Results allow reporting aPrE of 1.44%, showing an excellent correlation between them...
121 p.Segmentation of MRI data is required for many applications, such as the comparison of differen...
121 p.Segmentation of MRI data is required for many applications, such as the comparison of differen...
To ameliorate the measure of segmentation methods, a contrastive strategy of the hybrid segmentation...
Through this work we propose a computational technique forthe segmentation of a brain tumor, identif...
This work focuses the attention on the automatic segmentation of meningioma from multispectral brain...
This work focuses the attention on the automatic segmentation of meningioma from multispectral brain...
This work focuses the attention on the automatic segmentation of meningioma from multispectral brain...
This work focuses the attention on the automatic segmentation of meningioma from multispectral brain...
Through this work we propose a computational technique for the segmentation of a brain tumor, ident...
Rationale and Objectives—Manual segmentation of brain tumors from magnetic resonance (MR) images is ...
BackgroundMeningioma is the commonest primary brain tumour. Volumetric post-contrast magnetic resona...
Segmentation is a core process for automatic detection and identification of brain tumors as it ...
Through this work we propose a computational techniquefor the segmentation of magnetic resonance ima...
Through this work we propose a computational techniquefor the segmentation of magnetic resonance ima...
To detect the tumor in the brain is very important task but the major problem occurred is that its v...
121 p.Segmentation of MRI data is required for many applications, such as the comparison of differen...
121 p.Segmentation of MRI data is required for many applications, such as the comparison of differen...
To ameliorate the measure of segmentation methods, a contrastive strategy of the hybrid segmentation...
Through this work we propose a computational technique forthe segmentation of a brain tumor, identif...
This work focuses the attention on the automatic segmentation of meningioma from multispectral brain...
This work focuses the attention on the automatic segmentation of meningioma from multispectral brain...
This work focuses the attention on the automatic segmentation of meningioma from multispectral brain...
This work focuses the attention on the automatic segmentation of meningioma from multispectral brain...
Through this work we propose a computational technique for the segmentation of a brain tumor, ident...
Rationale and Objectives—Manual segmentation of brain tumors from magnetic resonance (MR) images is ...
BackgroundMeningioma is the commonest primary brain tumour. Volumetric post-contrast magnetic resona...
Segmentation is a core process for automatic detection and identification of brain tumors as it ...
Through this work we propose a computational techniquefor the segmentation of magnetic resonance ima...
Through this work we propose a computational techniquefor the segmentation of magnetic resonance ima...
To detect the tumor in the brain is very important task but the major problem occurred is that its v...
121 p.Segmentation of MRI data is required for many applications, such as the comparison of differen...
121 p.Segmentation of MRI data is required for many applications, such as the comparison of differen...
To ameliorate the measure of segmentation methods, a contrastive strategy of the hybrid segmentation...