A Brain MRI/SPECT Registration System Using an Adaptive Similarity Metric: Application on the Evaluation of Parkinson’s Disease. In: Gagalowicz A, Philips W, editors. Computer Vision/Computer Graphics Collaboration Techniques. Berlin: Springer Berlin Heidelberg; 2007. pp. 235-46. [DOI: 10.1007/978-3-540-71457-6_22]

Multi-image registration for evaluating the 99mTc-TRODAT-1 of Parkinson's rat model

Study on small animal model using multiple imaging is an important procedure in medicine and physiology. Recently, Single Photon Emission Computed Tomography (SPECT) of dopamine transporter with (99cm)Tc-TRODA-1 has been proved to be a valuable and feasible mean of assessing the integrity of dopamine neurons. In this paper, an image registration algorithm for MRI and SPECT is proposed to evaluate the changes of a Parkinson's rat in brain organization and function. In addition, an automatic labeling algorithm which highlights striatum is necessary because manually segmenting these tissues from MRI is usually time consuming. As a result, we have built a computer-aid clinical diagnosis system which automates all the processes. This paper provides effective evaluation of Parkinson's symptoms by calculating the values of binding potentials for dopamine for quantification. Experimental result shows that the performance of the proposed method is better than the previous approach based on automated image registration.

Computer-aided evaluation system for Parkinson's disease using image registration and labeling

Single photon emission computed tomography image (SPECT) of dopamine transporter with 99mTc-TRODAT-1 has recently been proposed to be a valuable and feasible means of assessing the integrity of dopamine neurons. In order to measure the specific-to-nonspecific binding ratio of the nuclear medicine within the specific-binding tissues, i.e. putamens and caudate nuclei, the corresponding MRI is needed to be registered to SPECT for bounding the regions of interest. Therefore, an automatic labeling algorithm which enables contouring the putamens and caudate nuclei is necessary because segmenting these tissues manually from MRI costs tons of time and energy of physicians. We have built a computer-aided clinical diagnosis system which integrates MRI/SPECT registration and MRI labeling for the evaluation of Parkinson's disease. Clinical MRI and SPECT data including eighteen healthy subjects and thirteen patients were involved to validate the performance of the proposed system.