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Medical Image Compression on a Multi ROI with Edge Feature Preserving

Published on None 2011 by T M P Rajkumar, Dr. Mrityunjaya V Latte
journal_cover_thumbnail
International Conference on VLSI, Communication & Instrumentation
Foundation of Computer Science USA
ICVCI - Number 12
None 2011
Authors: T M P Rajkumar, Dr. Mrityunjaya V Latte
8706c864-5d16-4732-9722-e2c3832e1610

T M P Rajkumar, Dr. Mrityunjaya V Latte . Medical Image Compression on a Multi ROI with Edge Feature Preserving. International Conference on VLSI, Communication & Instrumentation. ICVCI, 12 (None 2011), 13-19.

@article{
author = { T M P Rajkumar, Dr. Mrityunjaya V Latte },
title = { Medical Image Compression on a Multi ROI with Edge Feature Preserving },
journal = { International Conference on VLSI, Communication & Instrumentation },
issue_date = { None 2011 },
volume = { ICVCI },
number = { 12 },
month = { None },
year = { 2011 },
issn = 0975-8887,
pages = { 13-19 },
numpages = 7,
url = { /proceedings/icvci/number12/2717-1470/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on VLSI, Communication & Instrumentation
%A T M P Rajkumar
%A Dr. Mrityunjaya V Latte
%T Medical Image Compression on a Multi ROI with Edge Feature Preserving
%J International Conference on VLSI, Communication & Instrumentation
%@ 0975-8887
%V ICVCI
%N 12
%P 13-19
%D 2011
%I International Journal of Computer Applications
Abstract

Our objective is to design, implement and verify a Multi Region of Interest (ROI) Based Medical Image compression with Edge Feature Preserving based on SPIHT, JPEG-2000 and Canny Edge Detection.As medical/biological imaging facilities move towards complete film-less imaging, compression plays a key role. Although lossy compression techniques yield high compression rates, the medical community has been reluctant to adopt these methods, largely for legal reasons, and has instead relied on lossless compression techniques that yield low compression rates. The true goal is to maximize compression while maintaining clinical relevance and balancing legal risk. In this paper Algorithm developed has following advantages. 1.High compression ratio, keeping the quality of ROIs. 2. Algorthm explains the Gibbs effect and improves the quality of image reconstruction. 3. Algorithm can be used for remote medical image compression, and transfer.

References
  1. I lias Manglogianais,George Kormentazs,Thomas Pliakas “Wavelet Based Image CompressionWith ROI coding”, IEEE Transactions on Information Technology In Biomedicine,Volume 14,No4,July2009,pp458-465.
  2. Li-bao Zhang1 and Xian-chuan Yu “New Region of Interest Image Coding UsingGeneral Layered Bitplane Shift for MedicalImage Compression”,”International Journal of Computational Intelligence Research.”, Volume.3, No. 1 August 2007, pp. 97-104
  3. Rafael C.Gonzalez,Richard E Woods,StevenLEddins “Digital Image Processing”, PEARSON EDUCATION ,First Impression ,2006
  4. http://www.springerlink.com/content/l470300418588729/
Index Terms

Computer Science
Information Sciences

Keywords

Region of Interest Compression Ratio Peak Signal to Noise Ratio Mean Square Error Canny edge Detection