• Aucun résultat trouvé

[PDF] Top 20 Trimmed-likelihood estimation for focal lesions and tissue segmentation in multisequence MRI for multiple sclerosis.

Has 10000 "Trimmed-likelihood estimation for focal lesions and tissue segmentation in multisequence MRI for multiple sclerosis." found on our website. Below are the top 20 most common "Trimmed-likelihood estimation for focal lesions and tissue segmentation in multisequence MRI for multiple sclerosis.".

Trimmed-likelihood estimation for focal lesions and tissue segmentation in multisequence MRI for multiple sclerosis.

Trimmed-likelihood estimation for focal lesions and tissue segmentation in multisequence MRI for multiple sclerosis.

... automatic segmentation methods for MS lesions have been presented that can be classified in two categories: supervised or ...MS lesions [11], [12], [13], ...segmented and on the ... Voir le document complet

14

Robust Detection of Multiple Sclerosis Lesions from Intensity-Normalized Multi-Channel MRI

Robust Detection of Multiple Sclerosis Lesions from Intensity-Normalized Multi-Channel MRI

... difficult for the radiologist when the number of MR sequences grows ...automatic/semi-automatic segmentation of MS lesions using ...lesion segmentation includes Gaussian Mixture Modeling (GMM) ... Voir le document complet

8

Automatic Multiple Sclerosis lesion segmentation from Intensity-Normalized multi-channel MRI

Automatic Multiple Sclerosis lesion segmentation from Intensity-Normalized multi-channel MRI

... (GM) and Cerebrospinal Fluid (CSF). MS lesions are considered as outliers of this ...Maximum Likelihood Estimator (MLE) proposed by Notsu et ...This estimation is based on the -loss function ... Voir le document complet

8

Detection of Multiple Sclerosis Lesions using Sparse Representations and Dictionary Learning

Detection of Multiple Sclerosis Lesions using Sparse Representations and Dictionary Learning

... of Multiple Sclerosis (MS) lesions is a challenging task pertaining to the requirement of neurological experts and high intra- and inter-observer ...supervised and unsupervised ... Voir le document complet

10

Classification of Multiple Sclerosis Lesions using Adaptive Dictionary Learning

Classification of Multiple Sclerosis Lesions using Adaptive Dictionary Learning

... signals in a low-dimensional subspace and the development of effi- cient sparse coding and dictionary learning techniques offer a great advantage in medical image ...techniques in ... Voir le document complet

18

Automatic multiple sclerosis lesion segmentation with P-LOCUS

Automatic multiple sclerosis lesion segmentation with P-LOCUS

... lesion segmentation is important for diagnosis, prognosis, and patient ...consuming and subjective nature of manual ...demand for large-scale multi-center clinical research studies that ... Voir le document complet

5

Spatial distribution of multiple sclerosis lesions in the cervical spinal cord

Spatial distribution of multiple sclerosis lesions in the cervical spinal cord

... Kangoo and Percy McDonald for fruitful ...acknowledged for sharing data: Bailey Lyttle, Ben Conrad and Bennett Landman (Vanderbilt University); Marie-Pierre Ranjeva (CHU Timone); OFSEP ... Voir le document complet

15

Multiple Sclerosis lesion segmentation using an automatic multimodal Graph Cuts: Multiple Sclerosis lesion segmentation using an automatic multimodal Graph Cuts

Multiple Sclerosis lesion segmentation using an automatic multimodal Graph Cuts: Multiple Sclerosis lesion segmentation using an automatic multimodal Graph Cuts

... technique in several medical domains. We propose to automate the Graph Cuts in order to automatically segment Multiple Sclerosis (MS) lesions in ...approach in order to ... Voir le document complet

10

MRI predictors of cognitive outcome in early multiple sclerosis.

MRI predictors of cognitive outcome in early multiple sclerosis.

... deficiencies and several magnetic resonance imaging (MRI) markers, including lesion load (LL), diffuse brain abnormalities and brain atrophy, has been investigated ...time and the value of ... Voir le document complet

9

Multiple Sclerosis Lesions Evolution in Patients with Clinically Isolated Syndrome

Multiple Sclerosis Lesions Evolution in Patients with Clinically Isolated Syndrome

... present in a specific ...lesion and final patient clusters are ...features for a second layer clustering at the patient ...clustering and GMM 10 ...algorithm in the proposed ... Voir le document complet

9

Combining Robust Expectation Maximization and Mean Shift algorithms for Multiple Sclerosis Brain Segmentation

Combining Robust Expectation Maximization and Mean Shift algorithms for Multiple Sclerosis Brain Segmentation

... global and meaningful segmentation ...unsupervised and non-parametric gradient density estimation algorithm that has been successfully applied in clustering, segmentation ... Voir le document complet

11

Adaptation and evaluation of the multiple organs OSD for T2 MRI prostate segmentation

Adaptation and evaluation of the multiple organs OSD for T2 MRI prostate segmentation

... T2 MRI prostate imaging is now widely used for locating and identifying the prostate cancer by ...targets for prostate biopsy. Prostate MRI also plays an important role in ... Voir le document complet

5

Fully automated segmentation of the cervical cord from T1-weighted MRI using PropSeg: Application to multiple sclerosis

Fully automated segmentation of the cervical cord from T1-weighted MRI using PropSeg: Application to multiple sclerosis

... reduction in the SC cross-sectional area (CSA) over time, can be measured by means of image segmentation using magnetic resonance imaging ...However, segmentation methods have been limited by factors ... Voir le document complet

8

Multiple Sclerosis lesion segmentation using an automated multimodal Graph Cut

Multiple Sclerosis lesion segmentation using an automated multimodal Graph Cut

... voxel and is connected to two others nodes representing the object class for MS lesions and the background class for normal appearing brain tissues ...[6] and depend on the ... Voir le document complet

8

Probabilistic Atlas and Geometric Variability Estimation to Drive Tissue Segmentation

Probabilistic Atlas and Geometric Variability Estimation to Drive Tissue Segmentation

... randomly. For the pre-processing, we use BET [ 31 ] to delete the non-brain tissue from the images of the database ...75% for each tissue type. The rate for GM is better than SPM8 ... Voir le document complet

27

Serum GFAP in multiple sclerosis: correlation with disease type and MRI markers of disease severity

Serum GFAP in multiple sclerosis: correlation with disease type and MRI markers of disease severity

... with multiple sclerosis disease severity as well as treatment ...(s-GFAP) and neurofilament light chain (s-NfL) in a cohort of 129 multiple sclerosis (MS) ...progressive ... Voir le document complet

6

Automatic Detection and Segmentation of Evolving Processes in 3D Medical Images: Application to Multiple Sclerosis

Automatic Detection and Segmentation of Evolving Processes in 3D Medical Images: Application to Multiple Sclerosis

... Automatic Detection and Segmentation of Evolving Processes in 3D Medical Images: Application to Multiple Sclerosis David Rey, Gérard Subsol, Hervé Delingette, Nicholas Ayache.. To cite t[r] ... Voir le document complet

23

Distributed local MRF models for tissue and structure brain segmentation

Distributed local MRF models for tissue and structure brain segmentation

... local estimation as a preprocessing step to estimate a nonuniformity model and then restore the image [16], or use redundant information to ensure consistency and smoothness between local estimated ... Voir le document complet

19

Kullback Proximal Algorithms for Maximum Likelihood Estimation

Kullback Proximal Algorithms for Maximum Likelihood Estimation

... Unit´e de recherche INRIA Lorraine, Technopˆole de Nancy-Brabois, Campus scientifique, ` NANCY 615 rue du Jardin Botanique, BP 101, 54600 VILLERS LES Unit´e de recherche INRIA Rennes, Ir[r] ... Voir le document complet

22

Predicting PET-derived Demyelination from Multimodal MRI using Sketcher-Refiner Adversarial Training for Multiple Sclerosis

Predicting PET-derived Demyelination from Multimodal MRI using Sketcher-Refiner Adversarial Training for Multiple Sclerosis

... source and the target modalities. For example, Burgos et ...ages in the atlas database are registered to the given ...CT in the atlas database to the given MRI ...accuracy and ... Voir le document complet

16

Show all 10000 documents...