PMID- 22608347
OWN - NLM
STAT- MEDLINE
DCOM- 20121214
LR  - 20120618
IS  - 1879-0534 (Electronic)
IS  - 0010-4825 (Linking)
VI  - 42
IP  - 7
DP  - 2012 Jul
TI  - Medical ultrasound image compression using contextual vector quantization.
PG  - 743-50
LID - 10.1016/j.compbiomed.2012.04.006 [doi]
AB  - With ever increasing use of medical ultrasound (US) images, a challenge exists to 
      deal with storage and transmission of these images while still maintaining high 
      diagnostic quality. In this article, a state-of-the-art context based method is 
      proposed to overcome this challenge called contextual vector quantization (CVQ). 
      In this method, a contextual region is defined as a region containing the most 
      important information and must be encoded without considerable quality loss. 
      Attempts are made to encode this region with high priority and high resolution 
      (low compression ratio and high bit rate) CVQ algorithm; and the background, 
      which has a lower priority, is separately encoded with a low resolution (high 
      compression ratio and low bit rate) version of the CVQ algorithm. Finally both of 
      the encoded contextual region and the encoded background region is merged 
      together to reconstruct the output image. As a result, very good diagnostic image 
      quality with lower image size and enhanced performance parameters including mean 
      square error (MSE), pick signal to noise ratio (PSNR) and coefficient of 
      correlation (CoC) are gained. The experimental results show that the proposed CVQ 
      methodology is superior as compared to other existing methods (general methods 
      such as JPEG and JPEG2K, and ROI based methods such as EBCOT and CSPIHT) in terms 
      of measured performance parameters. This makes CVQ compression method a feasible 
      technique to overcome storage and transmission limitations.
CI  - Copyright (c) 2012 Elsevier Ltd. All rights reserved.
FAU - Hosseini, Seyed Morteza
AU  - Hosseini SM
AD  - Department of Computer Engineering, Faculty of Engineering, University of 
      Isfahan, Isfahan, Iran. mhosayny@gmail.com
FAU - Naghsh-Nilchi, Ahmad-Reza
AU  - Naghsh-Nilchi AR
LA  - eng
PT  - Journal Article
DEP - 20120517
PL  - United States
TA  - Comput Biol Med
JT  - Computers in biology and medicine
JID - 1250250
SB  - IM
MH  - *Algorithms
MH  - Data Compression/*methods
MH  - Humans
MH  - Image Processing, Computer-Assisted/*methods
MH  - Signal-To-Noise Ratio
MH  - Ultrasonography/*methods
EDAT- 2012/05/23 06:00
MHDA- 2012/12/15 06:00
CRDT- 2012/05/22 06:00
PHST- 2011/06/15 00:00 [received]
PHST- 2012/03/07 00:00 [revised]
PHST- 2012/04/24 00:00 [accepted]
PHST- 2012/05/22 06:00 [entrez]
PHST- 2012/05/23 06:00 [pubmed]
PHST- 2012/12/15 06:00 [medline]
AID - S0010-4825(12)00072-8 [pii]
AID - 10.1016/j.compbiomed.2012.04.006 [doi]
PST - ppublish
SO  - Comput Biol Med. 2012 Jul;42(7):743-50. doi: 10.1016/j.compbiomed.2012.04.006. 
      Epub 2012 May 17.