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#926Getting Started with Medical Image Processing Analysis and Visualization (MIPAV)
 
Description:
This class will cover a new release of the basic functionality of the MIPAV application. MIPAV is a platform-independent image processing and visualization program that assists researchers with extracting quantitative information from various medical imaging modalities. MIPAV is designed to be both an application and an Application Programming Interface (API) for the development and incorporation of new and innovative image processing, registration, and visualizations. As an application, MIPAV provides the researcher with a ready-made, general-purpose image analysis application to meet the majority of requirements of many researchers. Using MIPAV's standard user-interface and analysis tools, researchers can easily share research data and analysis, thereby enhancing their ability to research, diagnose, monitor, and treat medical disorders.
 
Objectives:
Topics to be covered include using MIPAV for the following:
  • Reading/writing DICOM images
  • Reading/writing MINC, Analyze, Tiff and raw images
  • Segmentation
  • Registration
  • Visualization
Who should attend:
NIH staff with an interest in image segmentation, quantification and visualization
 
Instructor(s):
Dr. Matthew McAuliffe, Division of Computational Bioscience, CIT
 
Time Required:
3 hours
 
Sections Available:
-- Concluded -- 926-09F October 20 9:00 - 12:00 Building 12A, Room B51
 
NOTE: Although this course has already taken place, we'll put you on a waiting list for the next available session.

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