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RSNA 2003 infoRAD > Automated MR Brain Image Study Summarization
 
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Automated MR Brain Image Study Summarization

  DATE: Sunday, November 30 2003 - Friday, December 05 2003
  START TIME: 07:00 AM
  END TIME: 10:00 PM
  LOCATION: Lakeside Center - InfoRAD Exhibits - Space 9122DS-i
  CODE: 9122DS-i
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PARTICIPANTS
PRESENTER
Usha Sinha PhD
Los Angeles , CA
 
CO-AUTHOR
Lynn Thompson MS
 
Suzie El-Saden MD
 
Siamak Ardekani MS
 
John David Dionisio PhD
 
Hooshang Kangarloo MD
 

Keywords
Brain
Magnetic resonance (MR), image processing
Walks Thru Week
infoRAD
 
Abstract:

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A MR brain image study consists of several image series obtained at different contrast and resolution. The study can however be summarized by a few relevant slices that document the patient condition effectively. Summarization is equivalent to a clinical compression and can be used in teaching files, for efficient integration into an electronic medical record, and for referring physicians. Automated image summarization is based on a novel combination of text and image processing techniques: (i) structured text related to patient presenting symptom and/or reason for scan is processed using expert rules to infer the differential diagnosis, relevant structure (defined as the location of the abnormality), optimum orientation/contrast of the images, and (ii) automated image registration of the patient study to a labeled customizable atlas to locate structures within the patient images. The MR atlas is customizable for contrast and intensity to match the current patient data to improve the accuracy of registration. For a given brain MR image study and patient presentation, the module will automatically identify the relevant slices showing the abnormality.

 

 


Learning Objectives:
*Image registration methods to automatically label a MR brain study. *Image synthesis of atlas to simulate contrast of patient study using known MR signal intensity dependences. *Mapping of patient presenting condition to anatomical location of abnormality, optimum image presentation. *Relevant image selection from MR study.
Questions about this event email: usinha@itmedicine.net