A brain MRI/SPECT registration system using an adaptive similarity metric: application on the metric evaluation of Parkinson's disease

  • Authors:

  • Jiann-Der Lee;Chung-Hsien Huang;Cheng-Wei Chen;Yi-Hsin Weng;Kun-Ju Lin;Chin-Tu Chen

  • Affiliations:

  • Department of Electrical Engineering, Chang Gung University, Tao-Yuan, Taiwan;Department of Electrical Engineering, Chang Gung University, Tao-Yuan, Taiwan;Department of Electrical Engineering, Chang Gung University, Tao-Yuan, Taiwan;Department of Neurology, Chang Gung Memorial Hospital, and University, Taipei, Taiwan;Molecular Image Center and Nuclear Medicine Department, Chang Gung Memorial Hospital, Linko, Taiwan;Department of Radiology and Committee on Medical Physics, The University of Chicago,

  • Venue:
  • MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
  • Year:
  • 2007

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Abstract

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 99mTc-TRODAT-1 binding, is 0.20 in the healthy group and 0.13 in the patient group via the proposed system.