The diagnosis of Parkinson's Disease is mainly clinical and sometimes misdiagnosis occurs due to the symptom similarity with other motor diseases. Besides, when those symptoms arise, the neurodegeneration is already in an advanced stage.

The main goal of the Parkinson Project is to develop a platform to aid in early diagnosis of Parkinson's Disease using medical imaging, clinical data, and artificial intelligence algorithms.

For that, medical imaging techniques such as Magnetic Resonance Imaging (MRI) and Single Photon Emission Computed Tomography (SPECT) will be processed with several processing techniques in order to obtain imaging biomarkers and connectivity information regarding the disease. Beyond imaging data, clinical data will also be analysed using data mining techniques.

This research uses Artificial Intelligence algorithms such as Convolutional Neural Networks to reduce the need to manually feature extraction. Besides, it will also provide a score useful for the diagnosis.