An efficient low complexity lossless coding algorithm for medical images

S. E. Ghrare, M. A Mohd Ali, K. Jumari, Mahamod Ismail

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

Problem statement: Nowadays a large number of various medical images are generated from hospitals and medical centers with sophisticated image acquisition devices, the movement toward digital images in radiology presents the problem of how to conveniently and economically store, retrieve and transmit the volume of digital images. Thus digital image data compression is necessary in order to solve this problem. So in a wide range of medical applications such as disease diagnostic and during the compression process, the loss of information is unacceptable; hence medical images are required to be at high resolution as possible. Instead of lossy compression with relatively high compression ratio, mathematical lossless compression methods are favored in this field. Approach: In this study, an efficient new lossless image coding algorithm using a simple technique was presented. Our coding algorithm was based on pixel redundancy reduction by formulating two matrices only, which were Gray Scale Matrix (GSM) and Binary Matrix (BM). These matrices had been used for coding and decoding processes. Results: Results showed that the maximum compression ratio achieved using the proposed method was 4:1, which was more efficient than the present lossless techniques, moreover the computational complexity is greatly simplified; therefore producing very fast coding and decoding. Conclusion: This algorithm was most suitable for those images where lossy compression was avoided such as medical images used for teleradiology and other telemedicine purposed and it can be applied to other medical modalities.

Original languageEnglish
Pages (from-to)1502-1508
Number of pages7
JournalAmerican Journal of Applied Sciences
Volume6
Issue number8
DOIs
Publication statusPublished - 2009

Fingerprint

Decoding
Telemedicine
Radiology
Image acquisition
Data compression
Medical applications
Image coding
Redundancy
Computational complexity
Pixels

Keywords

  • Lossless compression
  • Medical image
  • Telemedicine
  • Teleradiology

ASJC Scopus subject areas

  • General

Cite this

An efficient low complexity lossless coding algorithm for medical images. / Ghrare, S. E.; Ali, M. A Mohd; Jumari, K.; Ismail, Mahamod.

In: American Journal of Applied Sciences, Vol. 6, No. 8, 2009, p. 1502-1508.

Research output: Contribution to journalArticle

Ghrare, S. E. ; Ali, M. A Mohd ; Jumari, K. ; Ismail, Mahamod. / An efficient low complexity lossless coding algorithm for medical images. In: American Journal of Applied Sciences. 2009 ; Vol. 6, No. 8. pp. 1502-1508.
@article{f821b88e56ef43b1b172efe20a8d260c,
title = "An efficient low complexity lossless coding algorithm for medical images",
abstract = "Problem statement: Nowadays a large number of various medical images are generated from hospitals and medical centers with sophisticated image acquisition devices, the movement toward digital images in radiology presents the problem of how to conveniently and economically store, retrieve and transmit the volume of digital images. Thus digital image data compression is necessary in order to solve this problem. So in a wide range of medical applications such as disease diagnostic and during the compression process, the loss of information is unacceptable; hence medical images are required to be at high resolution as possible. Instead of lossy compression with relatively high compression ratio, mathematical lossless compression methods are favored in this field. Approach: In this study, an efficient new lossless image coding algorithm using a simple technique was presented. Our coding algorithm was based on pixel redundancy reduction by formulating two matrices only, which were Gray Scale Matrix (GSM) and Binary Matrix (BM). These matrices had been used for coding and decoding processes. Results: Results showed that the maximum compression ratio achieved using the proposed method was 4:1, which was more efficient than the present lossless techniques, moreover the computational complexity is greatly simplified; therefore producing very fast coding and decoding. Conclusion: This algorithm was most suitable for those images where lossy compression was avoided such as medical images used for teleradiology and other telemedicine purposed and it can be applied to other medical modalities.",
keywords = "Lossless compression, Medical image, Telemedicine, Teleradiology",
author = "Ghrare, {S. E.} and Ali, {M. A Mohd} and K. Jumari and Mahamod Ismail",
year = "2009",
doi = "10.3844/ajassp.2009.1502.1508",
language = "English",
volume = "6",
pages = "1502--1508",
journal = "American Journal of Applied Sciences",
issn = "1546-9239",
publisher = "Science Publications",
number = "8",

}

TY - JOUR

T1 - An efficient low complexity lossless coding algorithm for medical images

AU - Ghrare, S. E.

AU - Ali, M. A Mohd

AU - Jumari, K.

AU - Ismail, Mahamod

PY - 2009

Y1 - 2009

N2 - Problem statement: Nowadays a large number of various medical images are generated from hospitals and medical centers with sophisticated image acquisition devices, the movement toward digital images in radiology presents the problem of how to conveniently and economically store, retrieve and transmit the volume of digital images. Thus digital image data compression is necessary in order to solve this problem. So in a wide range of medical applications such as disease diagnostic and during the compression process, the loss of information is unacceptable; hence medical images are required to be at high resolution as possible. Instead of lossy compression with relatively high compression ratio, mathematical lossless compression methods are favored in this field. Approach: In this study, an efficient new lossless image coding algorithm using a simple technique was presented. Our coding algorithm was based on pixel redundancy reduction by formulating two matrices only, which were Gray Scale Matrix (GSM) and Binary Matrix (BM). These matrices had been used for coding and decoding processes. Results: Results showed that the maximum compression ratio achieved using the proposed method was 4:1, which was more efficient than the present lossless techniques, moreover the computational complexity is greatly simplified; therefore producing very fast coding and decoding. Conclusion: This algorithm was most suitable for those images where lossy compression was avoided such as medical images used for teleradiology and other telemedicine purposed and it can be applied to other medical modalities.

AB - Problem statement: Nowadays a large number of various medical images are generated from hospitals and medical centers with sophisticated image acquisition devices, the movement toward digital images in radiology presents the problem of how to conveniently and economically store, retrieve and transmit the volume of digital images. Thus digital image data compression is necessary in order to solve this problem. So in a wide range of medical applications such as disease diagnostic and during the compression process, the loss of information is unacceptable; hence medical images are required to be at high resolution as possible. Instead of lossy compression with relatively high compression ratio, mathematical lossless compression methods are favored in this field. Approach: In this study, an efficient new lossless image coding algorithm using a simple technique was presented. Our coding algorithm was based on pixel redundancy reduction by formulating two matrices only, which were Gray Scale Matrix (GSM) and Binary Matrix (BM). These matrices had been used for coding and decoding processes. Results: Results showed that the maximum compression ratio achieved using the proposed method was 4:1, which was more efficient than the present lossless techniques, moreover the computational complexity is greatly simplified; therefore producing very fast coding and decoding. Conclusion: This algorithm was most suitable for those images where lossy compression was avoided such as medical images used for teleradiology and other telemedicine purposed and it can be applied to other medical modalities.

KW - Lossless compression

KW - Medical image

KW - Telemedicine

KW - Teleradiology

UR - http://www.scopus.com/inward/record.url?scp=77950996995&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77950996995&partnerID=8YFLogxK

U2 - 10.3844/ajassp.2009.1502.1508

DO - 10.3844/ajassp.2009.1502.1508

M3 - Article

VL - 6

SP - 1502

EP - 1508

JO - American Journal of Applied Sciences

JF - American Journal of Applied Sciences

SN - 1546-9239

IS - 8

ER -