Literature DB >> 22549244

Texture-based medical image compression.

Vinayak K Bairagi1, Ashok M Sapkal, Ankita Tapaswi.   

Abstract

Image processing is one of the most researched areas these days due to the flooding of the internet with an overload of images. The noble medicine industry is not left untouched. It has also suffered with an excess of patient record storage and maintenance. With the advent of automation of the industries in the world, the medicine industry has sought to change and provide a more portable feel to it, leading to the fields of telemedicine and such. Our algorithm comes in handy in such scenarios where large amount of data needs to be transmitted over the network for perusal by another consultant. We aim for a visual quality approach in our algorithm rather than pixel-wise fidelity. We utilize parameters of edges and textures as the basic parameters in our compression algorithm.

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Year:  2013        PMID: 22549244      PMCID: PMC3553360          DOI: 10.1007/s10278-012-9472-8

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  6 in total

1.  Simultaneous structure and texture image inpainting.

Authors:  Marcelo Bertalmio; Luminita Vese; Guillermo Sapiro; Stanley Osher
Journal:  IEEE Trans Image Process       Date:  2003       Impact factor: 10.856

2.  Structure and texture filling-in of missing image blocks in wireless transmission and compression applications.

Authors:  Shantanu D Rane; Guillermo Sapiro; Marcelo Bertalmio
Journal:  IEEE Trans Image Process       Date:  2003       Impact factor: 10.856

3.  Filling-in by joint interpolation of vector fields and gray levels.

Authors:  C Ballester; M Bertalmio; V Caselles; G Sapiro; J Verdera
Journal:  IEEE Trans Image Process       Date:  2001       Impact factor: 10.856

4.  Determining hysteresis thresholds for edge detection by combining the advantages and disadvantages of thresholding methods.

Authors:  R Medina-Carnicer; A Carmona-Poyato; R Muñoz-Salinas; F J Madrid-Cuevas
Journal:  IEEE Trans Image Process       Date:  2010-01       Impact factor: 10.856

5.  Image inpainting by patch propagation using patch sparsity.

Authors:  Zongben Xu; Jian Sun
Journal:  IEEE Trans Image Process       Date:  2010-02-02       Impact factor: 10.856

6.  Texture-based identification and characterization of interstitial pneumonia patterns in lung multidetector CT.

Authors:  Panayiotis D Korfiatis; Anna N Karahaliou; Alexandra D Kazantzi; Cristina Kalogeropoulou; Lena I Costaridou
Journal:  IEEE Trans Inf Technol Biomed       Date:  2009-11-10
  6 in total

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