Parkinson's disease prediction using diffusion-based atlas approach

Roxana O. Teodorescu, Daniel Racoceanu, Nicolas Smit, Vladimir I. Cretu, Eng K. Tan, Ling L. Chan

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva


We study Parkinson's disease (PD) using an automatic specialized diffusion-based atlas. A total of 47 subjects, among who 22 patients diagnosed clinically with PD and 25 control cases, underwent DTI imaging. The EPIs have lower resolution but provide essential anisotropy information for the fiber tracking process. The two volumes of interest (VOI) represented by the Substantia Nigra and the Putamen are detected on the EPI and FA respectively. We use the VOIs for the geometry-based registration. We fuse the anatomical detail detected on FA image for the putamen volume with the EPI. After 3D fibers growing on the two volumes, we compute the fiber density (FD) and the fiber volume (FV). Furthermore, we compare patients based on the extracted fibers and evaluate them according to Hohen&Yahr (H&Y) scale. This paper introduces the method used for automatic volume detection and evaluates the fiber growing method on these volumes. Our approach is important from the clinical standpoint, providing a new tool for the neurologists to evaluate and predict PD evolution. From the technical point of view, the fusion approach deals with the tensor based information (EPI) and the extraction of the anatomical detail (FA and EPI).

Idioma originalInglés
Título de la publicación alojadaMedical Imaging 2010
Subtítulo de la publicación alojadaComputer-Aided Diagnosis
EditoresRonald M. Summers, Nico Karssemeijer
ISBN (versión digital)9780819480255
EstadoPublicada - 2010
Publicado de forma externa
EventoMedical Imaging 2010: Computer-Aided Diagnosis - San Diego, Estados Unidos
Duración: 16 feb. 201018 feb. 2010

Serie de la publicación

NombreProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN (versión impresa)1605-7422


ConferenciaMedical Imaging 2010: Computer-Aided Diagnosis
País/TerritorioEstados Unidos
CiudadSan Diego


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