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Integration of XNAT/PACS, DICOM, and Research Software for Automated Multi-modal Image Analysis.
Gao, Yurui; Burns, Scott S; Lauzon, Carolyn B; Fong, Andrew E; James, Terry A; Lubar, Joel F; Thatcher, Robert W; Twillie, David A; Wirt, Michael D; Zola, Marc A; Logan, Bret W; Anderson, Adam W; Landman, Bennett A.
Afiliação
  • Gao Y; Biomedical Engineering, Vanderbilt University, Nashville, TN, USA 37235 ; Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA 37235.
  • Burns SS; Vanderbilt Kennedy Center, Vanderbilt University, Nashville, TN, USA 37235.
  • Lauzon CB; Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA 37235 ; Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA 37235.
  • Fong AE; Blanchfield Army Community Hospital, Fort Campbell, KY, USA 42223.
  • James TA; Blanchfield Army Community Hospital, Fort Campbell, KY, USA 42223.
  • Lubar JF; Southeastern Biofeedback Institute, Inc., Knoxville, TN, USA 37996.
  • Thatcher RW; Applied Neuroscience, Inc., St. Petersburg, FL, USA 33708.
  • Twillie DA; Blanchfield Army Community Hospital, Fort Campbell, KY, USA 42223.
  • Wirt MD; Blanchfield Army Community Hospital, Fort Campbell, KY, USA 42223.
  • Zola MA; Blanchfield Army Community Hospital, Fort Campbell, KY, USA 42223.
  • Logan BW; Blanchfield Army Community Hospital, Fort Campbell, KY, USA 42223.
  • Anderson AW; Biomedical Engineering, Vanderbilt University, Nashville, TN, USA 37235 ; Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA 37235 ; Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, USA 37235.
  • Landman BA; Biomedical Engineering, Vanderbilt University, Nashville, TN, USA 37235 ; Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA 37235 ; Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA 37235 ; Radiology and Radiological Sciences, Vanderbilt Uni
Proc SPIE Int Soc Opt Eng ; 86742013 Mar 29.
Article em En | MEDLINE | ID: mdl-24386548
ABSTRACT
Traumatic brain injury (TBI) is an increasingly important public health concern. While there are several promising avenues of intervention, clinical assessments are relatively coarse and comparative quantitative analysis is an emerging field. Imaging data provide potentially useful information for evaluating TBI across functional, structural, and microstructural phenotypes. Integration and management of disparate data types are major obstacles. In a multi-institution collaboration, we are collecting electroencephalogy (EEG), structural MRI, diffusion tensor MRI (DTI), and single photon emission computed tomography (SPECT) from a large cohort of US Army service members exposed to mild or moderate TBI who are undergoing experimental treatment. We have constructed a robust informatics backbone for this project centered on the DICOM standard and eXtensible Neuroimaging Archive Toolkit (XNAT) server. Herein, we discuss (1) optimization of data transmission, validation and storage, (2) quality assurance and workflow management, and (3) integration of high performance computing with research software.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2013 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2013 Tipo de documento: Article