Medical imaging studies involve the analysis for large collections of complex information (multimodal MRI, CT, PET, etc). We facilitate clinical data exploration and hypothesis testing by developing and applying statistical analysis methods for the data that we extract through image analysis. We employ methods that analyze and correlate many different types of variables such as age, treatment, function, shape, volume, etc.
Infant MRI Head Coil Design
Improved MRI methodology for infant imaging: We study head/brain growth and create statistical models of neonates, 6mo, 1yr, 2yr and 4yr. Based on these models, the MGH group creates new parallel coils for the scanner. We then get these parallel images and combine them back with new signal processing.
Diffusion Tensor MRI Population Analysis
Diffusion tensor magnetic resonance imaging (DT-MRI) is relatively new imaging technique which provides new insight into the structure of brain white matter by measuring the local diffusion of water in the brain. In this project associated with the national alliance for medical image computing (NAMIC) images are combined from a population, as shown in figure 1, into a template atlas which reflects the average properties of the population. White matter bundles are extracted from in the template atlas to serve as a coordinate system for measuring diffusion properties and how they differ between populations. In a study of neurodevelopment in association with the CONTE center at University of North Carolina - Chapel Hill, an atlas was developed based on subjects at one and two years of age. Figure 2 shows fiber bundles extracted from this template atlas. Statistical comparison of the diffusion properties between one and two year olds indicates significant changes that may reflect underlying changes in myelination and axon development. Figure 3 shows differences in the fractional anisotropy (FA), a measure of diffusion tensors which is thought to reflect axon development, from one to two years. The red regions indicate the largest increase of the FA value.
The goal of this form of visualization is to identify the voxels in the diffusion tensor MRI volume that trace out paths linking two regions of the brain based on an optimization algorithm. The resulting paths may show the paths of functional communications between different parts of the brain.
Improved MRI methodology for infant imaging: We study head/brain growth and create statistical models of neonates, 6mo, 1yr, 2yr and 4yr. Based on these models, the MGH group creates new parallel coils for the scanner. We then get these parallel images and combine them back with new signal processing.
Diffusion tensor magnetic resonance imaging (DT-MRI) is relatively new imaging technique which provides new insight into the structure of brain white matter by measuring the local diffusion of water in the brain. In this project associated with the national alliance for medical image computing (NAMIC) images are combined from a population, as shown in figure 1, into a template atlas which reflects the average properties of the population. White matter bundles are extracted from in the template atlas to serve as a coordinate system for measuring diffusion properties and how they differ between populations. In a study of neurodevelopment in association with the CONTE center at University of North Carolina - Chapel Hill, an atlas was developed based on subjects at one and two years of age. Figure 2 shows fiber bundles extracted from this template atlas. Statistical comparison of the diffusion properties between one and two year olds indicates significant changes that may reflect underlying changes in myelination and axon development. Figure 3 shows differences in the fractional anisotropy (FA), a measure of diffusion tensors which is thought to reflect axon development, from one to two years. The red regions indicate the largest increase of the FA value.