Construction Of The Probability Map Of The Human Deep Brain Nuclei By Quantitative Susceptibility Mapping

Three dimensional brain atlas can provide useful anatomical reference for brain imaging data analysis.Through the automatic registration between subjects with cerebral template,brain atlas can effectively segment the brain into corresponding interest area.The structure and function of the human brain is complicated,and each part has its specificity.Standardization of space can reduce brain anatomical differences between individuals,so it is an important step in the human brain atlas studies.This dissertation was mainly based on quantitative susceptibility mapping and made a probability atlas which could be used for automatic segmentation of brain deep gray matter nuclei.This dissertation contains three aspects of contents:1.The basic theory and clinical applications of quantitative susceptibility mappingQuantitative susceptibility mapping(QSM)is a non-invasive MRI technique that measures the spatial distribution of magnetic susceptibility within an object.QSM computes the magnetic susceptibility from the phase images of gradient recalled echoes(GRE).This tomographic capability is unique as no other imaging techniques provide such an excellent tissue contrast,so QSM is widely used in the quantitative study of various neurodegenerative diseases,and the susceptibility change of the gray matter and myelin sheath throughout the brain development.As a novel medical image processing technology,QSM provides a strong guidance and convenience in all kind of clinical diagnosis and treatment of disease.2.The basic theory and applications of digital atlasImage analysis usually refers to processing of images by computer with the goal of finding what objects are presented in the image.Digital brain atlas have been used with success to help in the planning of neurosurgical interventions.Image registration is a vital problem in medical imaging.It has many potential applications in clinical diagnosis(Diagnosis of cardiac,retinal,pelvic,renal,abdomen,liver,tissue etc disorders).It is a process of aligning two images into a common coordinate system thus aligning them in order to monitor subtle changes between the two images.Image segmentation is also one of the critical tasks in automatic image analysis.It consists of subdividing an image into its constituent parts and extracting these parts of interest.Extensive research has been done in creating many different approaches and algorithms for image segmentation,but it is still difficult to assess whether one algorithm produces more accurate segmentations than another.The present study reviews different existing method for segmentation,as well as discuss their applicability,advantages and limitations.3.Construction of the probability map of the human deep brain nuclei by quantitative susceptibility mappingBased on Quantitative Susceptibility Mapping(QSM)technique,an auto-segment probabilistic atlas for the gray matter nuclei in deep brain was established in the present study.The QSM data from fifteen healthy subjects were acquired on a clinical 3T MRI scanner with a 12 channel matrix head coil.Ten subjects were randomly selected to create a gray matter nuclei atlas of the deep brain,and the remained five subjects were used to evaluate the effectiveness of the atlas.Specifically,the regions of interest(ROI)in six bilateral structures drawn manually by two raters were used as the gold standard,meanwhile,these corresponding ROIs were-automatically segmented by three kinds of atlas.To assess the accuracy of proposed segment approach,the probabilistic atlas was compared with both AAL and Johns Hopkins atlas by calculating the Dice coefficient and the susceptibility values in the auto-segment and manual-segment ROIs,respectively.We found that the Dice coefficient in our probability atlas was significantly higher than the AAL in the basal ganglia region and the Johns Hopkins atlas in the skull base and cerebellum,respectively.Moreover,the susceptibility values in our probability atlas were more closer to that of manual segment region compared with the other two atlases.In summary,the probability atlas based on the QSM images is more reliable than both AAL and Johns Hopkins atlas in the segment of gray matter nuclei of deep brain.This atlas may be effective to improve the efficiency of image analysis in the clinical research.