Abstract

The goal of this proposal is to improve and maintain our software DtiStudio. There are three main functions in this software. First, It reads and process data for diffusion tensor Imaging (DTI), a modern technology of magnetic resonance imaging (MRI). Unlike other MRI techniques, various types of images from DTI can be obtained only after complicated calculations and DTI data processing tools are not readily available. Second, the software provides interface for data analysis and quantification. Unlike conventional MRI, DTI contains 6 parameters in each pixel. Conventional MRI analysis software, therefore, is not always applicable for DTI data. Third, it allows 3D tract reconstruction of white matter tracts. This is again not a technique that can be readily developed by average users. On the other hand, DTI is becoming an important tool for various types of brain researches. The data acquisition scheme is now available in commercial MRI scanners and DTI data can be obtained easily as routine clinical practices. Needs for DTI data processing and analysis software is rapidly growing. Our DtiStudio now has approximately 3,000 registered users and the number is growing with an average rate of 40 users I month. The work load for software maintenance and user support is steadfastly growing while simultaneously new functions of the software are rapidly evolving. Based on these circumstances, we are asking for a fund to pursue following 4 aims;
Aim 1 : Establish a system for online manuals.
Aim 2 : Multi-platform support: The current DtlStudio supports only Windows platform. We will port DtlStudlo to Linux, Unix, and Mac OSX platform.
Aim 3 : Introduction of advanced software management and open source: The functionality of DtiStudio is ever growing, which makes it important to introduce advanced software management system for version tracking and working environment for multiple developers. This also provides an environment for open source.
Aim 4 : Upgrade to integrate new technologies.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS058299-02
Application #
7895613
Study Section
Special Emphasis Panel (ZRG1-BST-Q (01))
Program Officer
Liu, Yuan
Project Start
2009-08-01
Project End
2011-07-31
Budget Start
2010-08-01
Budget End
2011-07-31
Support Year
2
Fiscal Year
2010
Total Cost
$400,565
Indirect Cost

  Institution

Name
Johns Hopkins University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21218

  Publications

Faria, Andreia V; Oishi, Kenichi; Yoshida, Shoko et al. (2015) Content-based image retrieval for brain MRI: an image-searching engine and population-based analysis to utilize past clinical data for future diagnosis. Neuroimage Clin 7:367-76
Liang, Zifei; He, Xiaohai; Ceritoglu, Can et al. (2015) Evaluation of Cross-Protocol Stability of a Fully Automated Brain Multi-Atlas Parcellation Tool. PLoS One 10:e0133533
Li, Muwei; Ratnanather, J Tilak; Miller, Michael I et al. (2014) Knowledge-based automated reconstruction of human brain white matter tracts using a path-finding approach with dynamic programming. Neuroimage 88:271-81
Zhang, Yajing; Zhang, Jiangyang; Hsu, Johnny et al. (2014) Evaluation of group-specific, whole-brain atlas generation using Volume-based Template Estimation (VTE): application to normal and Alzheimer's populations. Neuroimage 84:406-19
Djamanakova, Aigerim; Tang, Xiaoying; Li, Xin et al. (2014) Tools for multiple granularity analysis of brain MRI data for individualized image analysis. Neuroimage 101:168-76
Djamanakova, Aigerim; Faria, Andreia V; Hsu, John et al. (2013) Diffeomorphic brain mapping based on T1-weighted images: improvement of registration accuracy by multichannel mapping. J Magn Reson Imaging 37:76-84
Mori, Susumu; Oishi, Kenichi; Faria, Andreia V et al. (2013) Atlas-based neuroinformatics via MRI: harnessing information from past clinical cases and quantitative image analysis for patient care. Annu Rev Biomed Eng 15:71-92
Li, Xin; Aggarwal, Manisha; Hsu, Johnny et al. (2013) AtlasGuide: software for stereotaxic guidance using 3D CT/MRI hybrid atlases of developing mouse brains. J Neurosci Methods 220:75-84
Yoshida, Shoko; Faria, Andreia V; Oishi, Kenichi et al. (2013) Anatomical characterization of athetotic and spastic cerebral palsy using an atlas-based analysis. J Magn Reson Imaging 38:288-98
Oishi, Kenichi; Mielke, Michelle M; Albert, Marilyn et al. (2012) The fornix sign: a potential sign for Alzheimer's disease based on diffusion tensor imaging. J Neuroimaging 22:365-74

Showing the most recent 10 out of 17 publications