Computer Vision
Image Registration Using Hierarchical B-Splines
IEEE Transactions on Visualization and Computer Graphics
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Multisensor Image Registration via Implicit Similarity
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiscale Joint Segmentation and Registration of Image Morphology
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Deformable Diffusion Tensor Registration for Fiber Population Analysis
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
Cerebral white matter integrity mediates adult age differences in cognitive performance
Journal of Cognitive Neuroscience
Incorporating DTI data as a constraint in deformation tensor morphometry between T1 MR Images
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
Registration of high angular resolution diffusion MRI images using 4th order tensors
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
A Nonparametric Approach for Histogram Segmentation
IEEE Transactions on Image Processing
MRI-based finite element simulation on radiofrequency ablation of thyroid cancer
Computer Methods and Programs in Biomedicine
MARGA: Multispectral Adaptive Region Growing Algorithm for brain extraction on axial MRI
Computer Methods and Programs in Biomedicine
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In this work we describe an integrated and automated workflow for a comprehensive and robust analysis of multimodal MR images from a cohort of more than hundred subjects. Image examinations are done three years apart and consist of 3D high-resolution anatomical images, low resolution tensor-valued DTI recordings and 4D resting state fMRI time series. The integrated analysis of the data requires robust tools for segmentation, registration and fiber tracking, which we combine in an automated manner. Our automated workflow is strongly desired due to the large number of subjects. Especially, we introduce the use of histogram segmentation to processed fMRI data to obtain functionally important seed and target regions for fiber tracking between them. This enables analysis of individually important resting state networks. We also discuss various approaches for the assessment of white matter integrity parameters along tracts, and in particular we introduce the use of functional data analysis (FDA) for this task.