Scheduled System Maintenance:
On May 6th, single article purchases and IEEE account management will be unavailable from 8:00 AM - 12:00 PM ET (12:00 - 16:00 UTC). We apologize for the inconvenience.
By Topic

Automatic putamen detection on DTI images. Application to Parkinson's Disease

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Sabau, A. ; Politeh. Univ. of Timisoara, Timisoara, Romania ; Teodorescu, R.O. ; Cretu, V.I.

The putamen, a complex structure located at the base of the forebrain [1], is connecting neuromotor fibres affected in neurodegenerative diseases, like Parkinson's Disease (PD). We study PD on a total of 47 subjects, with 22 patients clinically diagnosed with PD and 25 control cases. Using Diffusion Tensor Imaging (DTI), a type of Magnetic Resonance Imaging(MRI), we analyze the fractional anisotropy (FA) image stacks. These images hold the information relative to the dopamine flow, one of the neurotransmitters affecting the PD. The present article introduces a new method for the active automatic detection of the putamen. We evaluate our method using the manual tracing of the same anatomical region, validated by a medical expert (neurologist). Our method employs a geometrical approach that updates a classic active contour tracking method by eliminating the inter-patient variability. From the technical point of view we are providing an automated tool similar to an atlas approach, but with more versatility. From the medical point of view the importance of our approach resides in the possibility to provide a specific anatomical detail for further study: the putamen brain structure. This algorithm is part of PDFibAtl@s, our own PD detection system based on DTI image processing and analysis.

Published in:

Computational Cybernetics and Technical Informatics (ICCC-CONTI), 2010 International Joint Conference on

Date of Conference:

27-29 May 2010