Automated segmentation of basal ganglia and deep brain structures in MRI of Parkinson's disease - Université de Rennes Accéder directement au contenu
Article Dans Une Revue International Journal of Computer Assisted Radiology and Surgery Année : 2013

Automated segmentation of basal ganglia and deep brain structures in MRI of Parkinson's disease

Résumé

PURPOSE: Template-based segmentation techniques have been developed to facilitate the accurate targeting of deep brain structures in patients with movement disorders. Three template-based brain MRI segmentation techniques were compared to determine the best strategy for segmenting the deep brain structures of patients with Parkinson's disease. METHODS: T1-weighted and T2-weighted magnetic resonance (MR) image templates were created by averaging MR images of 57 patients with Parkinson's disease. Twenty-four deep brain structures were manually segmented on the templates. To validate the template-based segmentation, 14 of the 24 deep brain structures from the templates were manually segmented on 10 MR scans of Parkinson's patients as a gold standard. We compared the manual segmentations with three methods of automated segmentation: two registration-based approaches, automatic nonlinear image matching and anatomical labeling (ANIMAL) and symmetric image normalization (SyN), and one patch-label fusion technique. The automated labels were then compared with the manual labels using a Dice-kappa metric and center of gravity. A Friedman test was used to compare the Dice-kappa values and paired t tests for the center of gravity. RESULTS: The Friedman test showed a significant difference between the three methods for both thalami (p < 0.05) and not for the subthalamic nuclei. Registration with ANIMAL was better than with SyN for the left thalamus and was better than the patch-based method for the right thalamus. CONCLUSION: Although template-based approaches are the most used techniques to segment basal ganglia by warping onto MR images, we found that the patch-based method provided similar results and was less time-consuming. Patch-based method may be preferable for the subthalamic nucleus segmentation in patients with Parkinson's disease.
Fichier principal
Vignette du fichier
hal-00683777_edited.pdf (535.5 Ko) Télécharger le fichier
Heagelen_IJCARS2012_HAL.pdf (1.87 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-00683777 , version 1 (29-03-2012)
hal-00683777 , version 2 (30-03-2012)

Identifiants

Citer

Claire Haegelen, Pierrick Coupé, Vladimir Fonov, Nicolas Guizard, Pierre Jannin, et al.. Automated segmentation of basal ganglia and deep brain structures in MRI of Parkinson's disease. International Journal of Computer Assisted Radiology and Surgery, 2013, 8 (1), pp.99-110. ⟨10.1007/s11548-012-0675-8⟩. ⟨hal-00683777v2⟩
639 Consultations
959 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More