Literature DB >> 11818187

Software for efficient visualization and analysis of multiple, large, multi-dimensional data sets from magnetic resonance imaging.

Steve Uttecht1, Keith R Thulborn.   

Abstract

Comprehensive magnetic resonance imaging (MRI) protocols create multiple, large, multi-dimensional data sets that are challenging to review and interpret in an efficient manner. We report on a program called CliniViewer that uses a common data file format to display all files originating from the scanner and other post-processing programs in an integrated display matrix. The five rows of images and maps have general themes of Anatomic Images, Echo-Planar Images, Parametric Maps (derived from echo-planar images), Metabolic Images, and Non-Image Data, respectively. Each row of the matrix contains related image windows of individual MR acquisitions or maps derived from such acquisitions.An interpreter can quickly screen all images and then select any image from the display to create a separate daughter window incorporating a set of analysis tools for in-depth examination. Given that the images can be acquired in the same co-registered planes without moving the subject, regional analysis can be performed simultaneously across multiple MR image types and the corresponding maps, thereby integrating anatomic features with parametric properties. Color can be used to highlight parametric values that fall outside normal ranges to quickly identify abnormalities on each map. CliniViewer is an efficient environment for analyzing multiple images and maps from comprehensive clinical imaging protocols, aiding the neuroradiologist in providing an integrated interpretation of all available MR data for efficient clinical decision making. CliniViewer is compared to AnalyzeAVW and NIH Image, two popular MR image analysis tools. CliniViewer allows efficient clinical analysis of multiple images and maps from comprehensive clinical imaging protocols.

Mesh:

Year:  2002        PMID: 11818187     DOI: 10.1016/s0895-6111(01)00031-3

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


  1 in total

1.  Compare display schemes for lung nodule CT screening.

Authors:  Xiao Hui Wang; Janet E Durick; Amy Lu; David L Herbert; Carl R Fuhrman; Joan M Lacomis; Cynthia A Britton; Diane C Strollo; Sherry S Shang; Saraswathi K Golla; Walter F Good
Journal:  J Digit Imaging       Date:  2011-06       Impact factor: 4.056

  1 in total

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