| The international human brain imaging is continuously promoting multi-center and cross-regional research recently.Compared with a single center,multi-center research has the advantages of expanding data size,shortening the total acquisition time and so on.Diffusion weighted imaging(DWI)can detect tissue structure on a microscopic scale,and provide reference for the structure of neural tissue.Functional magnetic resonance imaging(fMRI)can non-invasively mapping the functional areas of the cerebral cortex.DWI and fMRI are of great value to humans in studying and revealing the mysteries of the brain,and are widely used in the study of multi-center research.However,significant heterogeneity in data quality exists among centers,it increases the complexity of subsequent data analysis.So,quality control(QC)is important in multi-center research.But traditional signal-center quality control program is difficult to apply to multi-center research due to the different equipment,sequences,and phantom.In addition,traditional quality control programs do not pay enough attention to DWI and fMRI,so there is no clear quality control scheme for DWI and fMRI.In order to ensure the reliability of multi-center DWI and fMRI research results,this paper studies the quality control of DWI and fMRI data.The main contents include:(1)Summarized the quality control indexs which are suitable for multicenter study.(2)Automatic QC detection algorithm was designed based on python,the comparison between manual calculation and software detection results was carried out to verify the accuracy of the automatic detection algorithm.The QC software with GUI interface is designed to facilitate the operator to conduct quality control analysis.(3)Analyzed the QC data of multicenter DWI and fMRI data using the QC software,provided examples and recommendations for similar multi-center research. |
