Literature DB >> 16524089

Perceptually lossless medical image coding.

David Wu1, Damian M Tan, Marilyn Baird, John DeCampo, Chris White, Hong Ren Wu.   

Abstract

A novel perceptually lossless coder is presented for the compression of medical images. Built on the JPEG 2000 coding framework, the heart of the proposed coder is a visual pruning function, embedded with an advanced human vision model to identify and to remove visually insignificant/irrelevant information. The proposed coder offers the advantages of simplicity and modularity with bit-stream compliance. Current results have shown superior compression ratio gains over that of its information lossless counterparts without any visible distortion. In addition, a case study consisting of 31 medical experts has shown that no perceivable difference of statistical significance exists between the original images and the images compressed by the proposed coder.

Entities:  

Mesh:

Year:  2006        PMID: 16524089     DOI: 10.1109/TMI.2006.870483

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  3 in total

1.  Development and evaluation of a novel lossless image compression method (AIC: artificial intelligence compression method) using neural networks as artificial intelligence.

Authors:  Hiroshi Fukatsu; Shinji Naganawa; Shinnichiro Yumura
Journal:  Radiat Med       Date:  2008-04

2.  A multicenter observer performance study of 3D JPEG2000 compression of thin-slice CT.

Authors:  Bradley J Erickson; Elizabeth Krupinski; Katherine P Andriole
Journal:  J Digit Imaging       Date:  2009-07-15       Impact factor: 4.056

3.  Visually Lossless JPEG 2000 for Remote Image Browsing.

Authors:  Han Oh; Ali Bilgin; Michael Marcellin
Journal:  Information (Basel)       Date:  2016-07-15
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.