Center for Scientific Computation in Imaging



Computational Methods and Analysis

Project Description

The Center for Scientific Computation in Imaging (CSCI) at UCSD is devoted to the development of addressing this critical junction between advanced scientific instrumentation and practical quantitative application through the development of novel principled theoretical approaches to the spatial and temporal exploration of scientific imaging data, and the development of efficient and accurate computational implementations of these new approaches. Our research mission is to provide cutting edge integrated analysis and visualization tools that are as easy to use as they are computationally sophisticated in order to facilitate the quantitative analysis of imaging data across a wide range of basic scientific and clinical disciplines. This basic research is supplemented by an educational mission to expand the understanding of data acquisition, analysis, and visualization to the formal education of students and researchers across a wide and ever expanding scope of scientific investigation, while providing the computational tools to both learn and apply these methods in their work. In addition, our public outreach is aimed at educating the public in the importance and utility of basic research in a wide range of application that have a direct impact on their daily lives, and motivating an interest in science among younger students, particularly in underserved populations, by demonstrating the fascinating world of imaging in science.


    Galinsky VL, Frank LR. Symplectomorphic registration with phase space regularization by entropy spectrum pathways. Magn Reson Med (accepted), 2018.

    Galinsky VL, Paulus M, Martinez A, Frank LR. Joint estimation of effective brain wave activation modes using EEG/MEG sensor arrays and multimodal MRI volumes. Neural Comput 30(7): 1725-1749, 2018.

    Galinsky VL, Frank LR. A unified theory of neuro-MRI data shows scale–free nature of connectivity modes. Neural Comput 29(6): 1441-1467, 2017. doi: 10.1162/NECO_a_00955

    Frank LR, Galinsky VL. Detecting spatio-temporal modes in multivariate data by entropy field decomposition. J Phys A 49: 395001, 2016.

    Frank LR, Galinsky VL. Dynamic multiscale modes of resting state brain activity detected by entropy field decomposition. Neural Comput, 28(9): 1769-1811, 2016.

    Galinsky VL, Frank LR. The lamellar structure of the brain fiber pathways. Neural Comput, 28: 2533-2556, 2016.

    Galinsky VL, Frank LR. Simultaneous multi-scale diffusion estimation and tractography guided by entropy spectrum pathways. IEEE Trans Med Imaging, 34: 1177-1193, 2015.

    Frank LR, Galinsky VL. Information pathways in a disordered lattice. Phys. Rev. E. 89: 032142, 2014.

    Galinsky VL, Frank LR. Automated segmentation and shape characterization of volumetric data. Neuroimage 92: 156-168, 2014.



Neurodegenerative Diseases

Project Description

CSCI has a long history of collaborations in clinical neuroscience with neuroimaging research focused on the neurological impacts of substance abuse and neurodegenerative diseases, such as traumatic brain injury (TBI) and mild cognitive impairment (MCI), and Alzheimer's disease (AD). Our most recent NIH-funded collaboration (R01AG054049), with Co-PI Dr. Mark Bondi in Psychiatry, is utilizing our QUEST-NI analysis and visualization methods to evaluate newly developed diagnostic and MRI metrics for measuring changes in an area of the brain where the first visible pathologic changes resulting from the onset of AD are believed to occur. This new approach has the potential to improve diagnostic and imaging precision in Preclinical AD and impact the prospective design of future studies, as well as promote new biomarker assessment modalities and fundamental shifts in therapeutic targets for AD.


    Sorg SF, Schiehser DM, Bondi MW, Luc N, Clark AL, Jacobson MW, Frank LR, Delano-Wood L. White matter microstructural compromise is associated with cognition but not posttraumatic stress disorder symptoms in military veterans with traumatic brain injury. Journal of Head Trauma Rehabilitation 31: 297-308, 2016.

    Sorg SF, Delano-Wood L, Luc N, Schiehser DM, Hanson KL, Nation, DA, Lanni E, Jak AJ, Lu K, Meloy MJ, Frank LR, Lohr JB, Bondi MW. White matter integrity in veterans with mild traumatic brain injury: Associations with executive function and loss of consciousness. Journal of Head Trauma Rehabilitation 29: 21-32, 2014.

    Delano-Wood L, Stricker NH, Sorg SF, Nation DA, Jak AJ, Woods SP, Libon DJ, Delis DC, Frank LR, Bondi MW. Posterior cingulum white matter disruption and its associations with verbal memory and stroke risk in mild cognitive impairment. Journal of Alzheimers Disease 29: 589–603, 2012.

    Krysl P, Bondi MW, Ward S, Frank LR. On sources of error in finite element simulation of blast effects in the human brain. Journal of Computational Nonlinear Dynamics 7: 031008, 2012.



Pulse Sequence Development

Project Description

dPFG FA improvement
Figure 1: FA Improvement

Working in conjunction with Dr Benjamin Zahneisen at Stanford University, we have developed a highly efficient multi band pulse sequence capable of acquiring multiple types of diffusion weighted (DW) MRI data, including high angular resolution single pulsed field gradient (sPFG) data, double pulsed field gradient (dPFG), and hyperecho sPFG. The pulse sequence is based on the highly efficient Extended Hybrid-Space SENSE for EPI which provides highly efficient off-resonance and eddy current correction using a joint interleaved blip-up/down reconstruction. This acquisition is significantly faster than the standard acquisition that require two (blip up & blip down) acquisitions, and also significantly enhances image quality as the distortions are corrected as part of the reconstruction process, rather than ex post facto. The resulting acquisition is not only significantly more time efficient, but shows a dramatic improvement in DWI image quality. This pulse sequence is currently being used in a range of basic and clinical research projects. Figure 1, on the right, shows FA maps (left) and directionally colored FA maps (right) from old (top) and new (bottom) pulse sequences. Marked improvement is evident.


High resolution, low distortion DTI remains one of the major challenges in MR pulse sequence development. In order to reduce the deleterious effects of the significant physiological motion in the human brain, single shot, slice selective (i.e., 2D) EPI has been widely adopted as the standard imaging sequence for human in vivo diffusion MRI. However, this limits the attainable spatial resolution, and is prone to susceptibility artifacts that significantly distort the images. In an earlier NIH-funded project (R01 MH064729), we developed methods for high spatial and angular resolution diffusion tensor imaging (DTI) in humans that overcomes these limitations in existing methods. We developed a novel high resolution, low distortion 3D Variable Density Spiral (VDS) Fast Spin Echo (FSE) diffusion tensor imaging (DTI) pulse sequence that allows higher spatial and angular resolution DTI and is able to image in regions of the human brain previously unattainable due to susceptibility distortions.


    Frank LR, Jung Y, Inati S, Tyszka JM, Wong EC. High efficiency, low distortion, 3D diffusion tensor imaging with variable density spiral fast spin echoes (3D DW VDS RARE). Neuroimage, 49: 1510-23, 2010.

    Tyszka JM, Frank LR. High-field diffusion MR histology: Image-based correction of eddy current ghosts in diffusion-weighted rapid acquisition with relaxation enhancement (DW-RARE). Magn Reson Med, 61: 728-33, 2009.