Imaging of dopamine transporters (DaT) has been introduced as a valuable tool to evaluate patients with several neuropsychiatrie disorders, such as Parkinson’s disease (PD). Over the last decade, several computer applications have been developed in order to facilitate the exploration of DaT images to clinicians, however they require a high interaction with the user to delimit regions of interest (ROIs) and to obtain a diagnosis. In this paper we show a full automatic computed aided diagnosis (CAD) system for Parkinson’s disease. We use a Partial Least Square scheme to decompose DaT images into scores and loading. Then, the scores with highest Fisher Discriminant Ratio are used as feature for a Support Vector Machine classifier that determines the state (normal of pathological) of a given DaT image. The evaluation of the system using a database with 178 images from controls and PD patients has produced accuracy rates of nearly 93%.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 firstname.lastname@example.org
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 email@example.com