Difference between revisions of "2016 Winter Project Week/Projects/BatchImageAnalysis"

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==Project Description==
 
==Project Description==
 
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{| class="wikitable"
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! style="text-align: left; width:27%" |  Objective
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! style="text-align: left; width:27%" |  Approach and Plan
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! style="text-align: left; width:27%" |  Progress and Next Steps
 
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|- style="vertical-align:top;"
! style="text-align: left; width:27%" |       Objective
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* Run feature detection code over a collection of medical images pulled from PACS
 
* Run feature detection code over a collection of medical images pulled from PACS
 
* Investigate a collection of ADC maps of neonates (diffusion MR)
 
* Investigate a collection of ADC maps of neonates (diffusion MR)
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* Use 3D SIFT code to see if health status can be detected in images
 
* Use 3D SIFT code to see if health status can be detected in images
 
* (if time) try text analysis of radiology reports
 
* (if time) try text analysis of radiology reports
 
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! style="text-align: left; width:27%" |       Approach, Plan
 
 
<!-- Add a bulleted list of key points -->
 
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* Use deidentified cohort of neonate images collected from MGH
 
* Use deidentified cohort of neonate images collected from MGH
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* Explore visualization options  
 
* Explore visualization options  
 
* (if time) integrate image features with analysis of radiology report text
 
* (if time) integrate image features with analysis of radiology report text
 
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! style="text-align: left; width:27%" |     Progress
 
 
<!-- Fill this out at the end of Project Week; describe what you did this week and what you plan to do next -->
 
<!-- Fill this out at the end of Project Week; describe what you did this week and what you plan to do next -->
 
*
 
*
 
 
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Revision as of 13:58, 24 December 2015

Home < 2016 Winter Project Week < Projects < BatchImageAnalysis

Key Investigators

  • Kalli Retzepi (MGH)
  • Yangming Ou (MGH)
  • Matt Toews (BWH)
  • Steve Pieper (BWH)
  • Sandy Wells (BWH)
  • Randy Gollub (MGH)

Project Description

Objective Approach and Plan Progress and Next Steps
  • Run feature detection code over a collection of medical images pulled from PACS
  • Investigate a collection of ADC maps of neonates (diffusion MR)
  • Patients labeled with age and health status (normal, mildly abnormal, severely abnormal)
  • Use 3D SIFT code to see if health status can be detected in images
  • (if time) try text analysis of radiology reports
  • Use deidentified cohort of neonate images collected from MGH
  • Install data and software on AWS, try StarCluster
  • Explore visualization options
  • (if time) integrate image features with analysis of radiology report text