A Brain MRI/SPECT Registration System Using an Adaptive Similarity Metric: Application on the Evaluation of Parkinson's Disease

Single photon emission computed tomography (SPECT) of dopamine transporters with 99mTc-TRODAT-1 has recently been proposed to provide valuable information of assessing the dopaminergic system. In order to measure the binding ratio of the nuclear medicine, registering magnetic resonance imaging (MRI) and SPECT image is a significant process. Therefore, an automated MRI/SPECT image registration algorithm of using an adaptive similarity metric is proposed. This similarity metric combines anatomic features characterized by specific binding (SB), the mean counts per voxel within the specific tissues, of nuclear medicine and distribution of image intensity characterized by the Normalized Mutual Information (NMI). In addition, we have also built a computer-aid clinical diagnosis system which automates all the processes of MRI/SPECT registration for further evaluation of Parkinson's disease. Clinical MRI/SPECT data from eighteen healthy subjects and thirteen patients are involved to validate the performance of the proposed system. Comparing with the conventional NMI-based registration algorithm, our system reduces the target of registration error (TRE) from <7 mm to approximate 4 mm. From the view point of clinical evaluation, the error of binding ratio, the ratio of specific-to-non-specific 99mTc-TRODAT-1 binding, is 0.20 in the healthy group and 0.13 in the patient group via the proposed system.