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3D Loss-less Multi-resolution Image Compression for Medical Images

  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 9608PACS-i
  CODE: 9608PACS-i
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PARTICIPANTS
PRESENTER
Sudipta Mukhopadhyay PhD
Bangalore India
 
CO-AUTHOR
S.V. Kumar MS
 
Vishram Nandedkar MS
 
Animesh Raparia
 
David Hou PhD
 
David Xu MS
 
et al
 

Keywords
Picture archiving and communication system (PACS)
Radiology, digital
Teleradiology
Walks Thru Week
infoRAD
 
Abstract:

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Radiologists are habituated to view scans one after another. So, compression algorithms for medical scan have been concentrated on 2D images. Today, PACS database is dominated by X-ray images (CR, DR, DX). Presently the image volume is increasing rapidly with the increase in speed of acquisition device and decrease in slice thickness. Soon, CT and MR will dominate the PACS database. It poses a big challenge to radiologists to sustain their productivity if they want to view the fine slices one after another. The other big challenge will be to transport such huge volume of data over network without undue delay. 3D image compression provides a promising approach to solve these problems at the same time. The extra dimension will provide more compressing allowing more efficient storage and transport over network. 3D data will allow radiologists to view voxel data rather than pixels. Using multi-resolution in axial dimension they can navigate quickly through low-resolution data (in axial direction) and on reaching the right place look at the high-resolution data and make the diagnosis. The asymmetric codec will help them to sustain their productivity and improve it further.

 


Learning Objectives:

3D compression algorithms exploit the redundancy of information in Z dimension to provide better compression ratio

3D compression algorithms exploit the redundancy of information in Z dimension to provide better compression ratio. The multi-resolution in z- dimension provides averaged frames. This will help radiologist to sustain its productivity and improve it while reading big volume scans. (S.M., S.B., and V.N., Employees, GE India Technology Centre; A.R., Employee, Wipro GE Medical Systems; D.H. and D.X.,  Employees, GE Medical Systems.)


Questions about this event email: Sudipta.M@geind.ge.com