A5062251252- Advanced Neuroimaging Techniques and Applications
- Functional Brain Connectivity Studies
- Advanced MRI Techniques and Applications
- Genetic Associations and Epidemiology
- Tensor decomposition and applications
- Schizophrenia research and treatment
- Multiple Sclerosis Research Studies
- Fetal and Pediatric Neurological Disorders
- Bipolar Disorder and Treatment
- Sparse and Compressive Sensing Techniques
- Child Abuse and Trauma
- Bone and Joint Diseases
- Genomic variations and chromosomal abnormalities
- Medical Image Segmentation Techniques
- Fractional Differential Equations Solutions
- Epigenetics and DNA Methylation
- Genetics and Neurodevelopmental Disorders
- MRI in cancer diagnosis
- Advanced Optimization Algorithms Research
- Neuroscience and Neuropharmacology Research
- Child and Adolescent Psychosocial and Emotional Development
- Simulation Techniques and Applications
- Numerical methods in inverse problems
- Autism Spectrum Disorder Research
- Stress Responses and Cortisol
Brigham and Women's Hospital
2019
Harvard University
2006-2019
University of Oslo
2012-2014
University of Bergen
2005-2011
Boston University
2007
Cerebrospinal fluid partial volume effect is a known bias in the estimation of Diffusion Tensor Imaging (DTI) parameters from diffusion MRI data. The Free‐Water model for data adds second compartment to DTI model, which explicitly accounts signal contribution extracellular free‐water, such as cerebrospinal fluid. As result obtained through free‐water are corrected effects, and thus better represent tissue microstructure. In addition, estimates fractional can be used monitor changes space....
Estimating white matter fiber pathways from a diffusion tensor MRI dataset has many important applications in medical research. However, the standard approach of performing tracking on single-tensor estimates per voxel is confounded by regions multiple different directions. Building previous work for estimating tensors MR value partitioning, we present here two-tensor tractography method that two acquired values, interpolated at each step path, and follows most aligned with current...
During the last years, many techniques for de-noising, segmentation and fiber-tracking have been applied to diffusion tensor MR image data (DTI) from human animal brains. However, evaluating such methods may be difficult on these since there is no gold standard regarding true geometry of brain anatomy or fiber bundles reconstructed in each particular case. In order study, validate compare various de-noising methods, a need (mathematical) phantom consisting semi-realistic images with...
In this work, we present a new algorithm for solving the augmented trust-region subproblem with set of additional linear inequality constraints. The method can be considered as generalization previously published [M. Rojas and T. Steihaug, An interior-point trust-region-based large-scale non-negative regularization, Inverse Problems 18(5) (2002), pp. 1291–1307]. We discuss types problems our formulation solve reproduce regularized inverse-problem results from image processing in general framework.
Multiparametric magnetic resonance imaging enables local assessment of tissue “signatures” in the aging brain. By proper alignment data we can for each voxel, or region interest (ROI) i obtain a pattern vector ×i =(×i1, ,×ip), where ×ij expresses property. Such vectors jointly be combined with test results from genotyping and cognitive evaluation, thereby give important differentiating information normal aging, mild impairment Alzheimers disease. The present work is feasibility study...