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Hans Johnson has received formal training in biomedical, electrical and computer engineering, which provides a solid foundation for his academic research objective of accelerating brain research through development of automated software processes. Johnson is the lead developer on 14 projects hosted by the Neuroinformatics Tools and Resources Clearing House. He is also the 13th most prolific contributor to the Insight Toolkit package and the president of the Insight Software Consortium. Johnson has been significantly involved in several imaging and informatics projects that focused on developing the tools necessary to monitor and manage large-scale, multi-site projects. In particular, he is the core leader for informatics of a 32-site, longitudinal study called PREDICT-HD that is funded by the National Institutes of Health.
Dawei Liu earned his doctorate degree in biostatistics from the University of Michigan in 2005 and came to the University of Iowa in 2008. In addition to his academic background in biostatics, Liu has extensive experience in structural, functional, and diffusion magnetic resonance image processing. He is particularly interested in the statistical analysis of neuroimaging data, especially the longitudinal structural and functional imaging data. Liu has been involved in the research activities of PREDICT-HD since 2009. He is currently working on the statistical analysis of structural imaging data using FreeSurfer and complex network analysis of resting state functional imaging data for PREDICT-HD.
Jatin Vaidya is an associate in the Department of Psychiatry at the University of Iowa. Jatin holds a doctorate degree in psychology and has completed a fellowship in neuroimaging of mental illness. His primary area of interest is in the neurobiology of emotion and motivation. Using structural and function imaging in conjunction with psychometric and behavioral indices, Jatin also examines how these processes change and develop over time and in relation to neurodegeneration.
Kathy Jones has worked in brain imaging research at the University of Iowa since 1993 and joined the Iowa Neuroimaging Consortium (INC) in 2008. Jones is the lead technician for developing the new automated neural network training set and has developed tracing reliability on basal ganglia structures, anterior cingulate, and hippocampus in 1.5 and 3T scans using Slicer 4.1 and Brains2. Using FreeSurfer 4.5, Brains2 and Slicer 4.1, she also reviews and edits imaging data sets of raw and processed scans in the automated neural network for TRACK-On HD and PREDICT-HD. Jones is reliable on structural landmarks documented by the Brains Constellation Detector project and paper.
In addition, Jones creates electronic and hard copy documentation of custom software and trains new users in a variety of software applications. She oversees functional magnetic resonance imaging acquisition for PREDICT-HD subjects, assists with regulatory compliance for the functional magnetic resonance imaging protocol, and monitors workflow to meet project deadlines. Jones is currently reviewing DWI raw images and DTIprep output as well as working to become reliable on posterior cingulate tracing.
Jacquie Marietta has worked in research at the University of Iowa since 1992 and joined the Iowa Neuroimaging Group (INC) in 2009. Marietta has developed tracing reliability of basal ganglia structures, anterior cingulate, and hippocampus in 1.5 and 3T scans using Slicer 4.1 and Brains2. She has also reviewed and edited imaging datasets of raw and processed scans for the automated neural network for TRACK-On HD and PREDICT-HD. Marietta currently works with DWI raw images and DTIprep output reviews. She is also working to become reliable on posterior cingulate tracing.
David Welch began working in medical radiation and internal sensing at Washington University where he was studying physics, specifically motion correction methods with radiation therapy treatment for lung cancer. As a graduate student in biomedical engineering at the University of Iowa, Welch studied longitudinal formation and rupture of brain aneurysm in addition to texture classification of tissue in CT images. He received his master's degree in 2010 for his work on a semi-automated approach to segmentation of small aneurysms in the presence of gradient-obfuscating artifacts. It was during his studies at the University of Iowa that he became interested in automated methods of medical imaging analysis, from segmentation and tissue classification to disease diagnosis and progression assessment.
Welch has over five years of experience as a research programmer using a variety of languages and technologies that include Python, C/C++, Bash, Ruby, Lisp, Java, MATLAB, PostgresSQL, XNAT, Nipype, and Git. He is active in the medical imaging open-source movement, specifically in the Slicer/ITK, VMTK, and Nipy communities. He is also an advocate of robust software standards and reproducible research in medical image analysis. In addition to his work at the University of Iowa, Welch volunteers with Iowa City's CoderDojo chapter, teaching local children to be coding ninjas instead of cowboys.
Kent Williams has been engaged in software development for the Iowa Neuroimaging Consortium (INC) since 2003. Williams work supports brain imaging research in the department, specifically the "Auto-Workgroup" image processing pipeline. This pipeline is used to process MRI, fMRI, and PET image scans to generate data needed for various research projects. He has worked on a variety of projects funded by grants, including the development of the Insight Toolkit, TRACK-On HD, and PREDICT-HD.
Williams received a bachelor's degree in English in 1981 and a master's degree in computer sciences in 1996. Prior to joining the department, Williams worked in the commercial software development world (most recently at LMS-CADSI, developing dynamic simulation software for mechanical engineering). His areas of expertise are in C++ development and in the complete software life-cycle (design, development, debugging, packaging, and maintenance).
Eric Axelson joined the Iowa Neuroimaging Consortium (INC) at the University of Iowa in 2003. Axelson has been the primary imaging research specialist on almost 10 major grants, including to multi-site studies. He has expertise in the preprocessing, quality control, and troubleshooting of automated neuroimaging pipelines developed by his group. Axelson has been the first to test new software and give feedback to developers on bugs and potential improvements. He is one of the main raters on the quality control effort, and his expertise drives the process improvements to capture more and more data. Axelson's experience with manual processing is valuable in troubleshooting problem data and correcting it for further automated processes. He is also charged with creating datasets for investigators and running small projects to investigate issues critical to his group and the consortium. Axelson has attended conferences and workshops over the years to further his knowledge base in neuroimaging, including four conferences by the Organization for Human Brain Mapping. Due to his long experience in the field and rapid processing abilities, he is vital near important deadlines as he can accelerate his group efforts.
Jessica Forbes began working for the Iowa Neuroimaging Consortium (INC) in late 2011. Forbes has over three years of programming experience and her skill set includes Python, Sqlite, Nipype, Bash, and MATLAB. She helped lead the development of the ANTS Template Building Nipype pipeline and has written several Python scripts for image processing. Forbes is in charge of FreeSurfer image quality reviews for PREDICT-HD and TRACK-On HD as well as the development of an in-house FreeSurfer image viewer that story quality assessments in a Sqlite database. She has created tutorials for editing FreeSurfer cortical labels and has taught several research assistants the process. Forbes has also processed and reviewed DTI images using Slicer 4.1 and is reliable in tracing human and mice brains using Brains2.
Forbes completed bachelor's degrees in biology and mathematics in May 2011. Before joining the University of Iowa, she participated in the AMGEN Scholars Research Program at the University of Washington in Seattle, Washington. Her project was to assess the spatial variability of a semi-automated method of glioma segmentation on magnetic resonance images. Forbes also completed two internships at Pacific Northwest National Laboratory, which focused on computational proteomics.
Eun Young (Regina) Kim received her Ph.D. In December 2013 from the Biomedical Engineering department at the University of Iowa. Kim began working for the Iowa Neuroimaging Consortium (INC) in late 2007. Kim's research focuses on segmentation of regions of interest with machine-learning, statistical techniques, and highly deformable registration in the auto-pipeline for large-scale and multi-site data. Her skill set includes: programming language like C/C++, Java, Python, Perl, Lisp, CLIPS, UNIX Shell scripting, TCL, XML, and SQL; source code management using SVM and Git; and statistical software including R, SAS, and MATLAB. Kim earned a mater's degree in biomedical engineering in 2010 and is the process of earning doctorate degree.
Joy Matsui completed Ph.D. Training in January 2014 from the Biomedical Engineering department at the University of Iowa. She continues to assist with diffusion weighted imaging analysis and interpretation as she completes medical school and becomes board-certified in diagnostic radiology. She believes this will further support her career in medical image processing research.
Matsui's current project and dissertation topic is to develop a pipeline to process and analyze longitudinal diffusion weighted imaging and clinical data collected from premanifest Huntington disease subject on an individual basis.
Ali Ghayoor earned his master’s degree in electrical engineering in 2010 and joined the Department of Psychiatry in early 2011. Ghayoor is currently pursuing his doctoral degree in electrical and computer engineering with a focus on medical image processing. His areas of interest include highly deformable and multi-level image registration, and automatic detection of anatomical landmarks in magnetic resonance imaging scans of the human brain for large-scale and multi-site data.
Ghayoor's areas of expertise are in variety of languages and technologies, including: C/C++, Python, Linux shell scripting, XML, HTML, MATLAB, and Git. Also, he is active in medical imaging open-source applications development and contributes in ITK developers’ community.