Efficient transmission of compressed data for remote volume visualization

Karthik Krishnan, Michael W Marcellin, Ali Bilgin, Mariappan S. Nadar

Research output: Contribution to journalArticle

49 Citations (Scopus)

Abstract

One of the goals of telemedicine is to enable remote visualization and browsing of medical volumes. There is a need to employ scalable compression schemes and efficient client-server models to obtain interactivity and an enhanced viewing experience. First, we present a scheme that uses JPEG2000 and JPIP (JPEG2000 Interactive Protocol) to transmit data in a multi-resolution and progressive fashion. The server exploits the spatial locality offered by the wavelet transform and packet indexing information to transmit, in so far as possible, compressed volume data relevant to the clients query. Once the client identifies its volume of interest (VOI), the volume is refined progressively within the VOI from an initial lossy to a final lossless representation. Contextual background information can also be made available having quality fading away from the VOI. Second, we present a prioritization that enables the client to progressively visualize scene content from a compressed file. In our specific example, the client is able to make requests to progressively receive data corresponding to any tissue type. The server is now capable of reordering the same compressed data file on the fly to serve data packets prioritized as per the client's request. Lastly, we describe the effect of compression parameters on compression ratio, decoding times and interactivity. We also present suggestions for optimizing JPEG2000 for remote volume visualization and volume browsing applications. The resulting system is ideally suited for client-server applications with the server maintaining the compressed volume data, to be browsed by a client with a low bandwidth constraint.

Original languageEnglish (US)
Article number1677725
Pages (from-to)1189-1199
Number of pages11
JournalIEEE Transactions on Medical Imaging
Volume25
Issue number9
DOIs
StatePublished - Sep 2006

Fingerprint

Wavelet Analysis
Telemedicine
Information Storage and Retrieval
Diptera
Servers
Visualization
Wavelet transforms
Decoding
Tissue
Bandwidth
Network protocols

Keywords

  • Code-block
  • Discrete wavelet transform (DWT)
  • Embedded coding
  • JPEG2000
  • JPIP
  • Precinct
  • Scalable compression

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology
  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Computational Theory and Mathematics

Cite this

Efficient transmission of compressed data for remote volume visualization. / Krishnan, Karthik; Marcellin, Michael W; Bilgin, Ali; Nadar, Mariappan S.

In: IEEE Transactions on Medical Imaging, Vol. 25, No. 9, 1677725, 09.2006, p. 1189-1199.

Research output: Contribution to journalArticle

@article{0cd22d7698bf4ad28027c0c5e7ec644f,
title = "Efficient transmission of compressed data for remote volume visualization",
abstract = "One of the goals of telemedicine is to enable remote visualization and browsing of medical volumes. There is a need to employ scalable compression schemes and efficient client-server models to obtain interactivity and an enhanced viewing experience. First, we present a scheme that uses JPEG2000 and JPIP (JPEG2000 Interactive Protocol) to transmit data in a multi-resolution and progressive fashion. The server exploits the spatial locality offered by the wavelet transform and packet indexing information to transmit, in so far as possible, compressed volume data relevant to the clients query. Once the client identifies its volume of interest (VOI), the volume is refined progressively within the VOI from an initial lossy to a final lossless representation. Contextual background information can also be made available having quality fading away from the VOI. Second, we present a prioritization that enables the client to progressively visualize scene content from a compressed file. In our specific example, the client is able to make requests to progressively receive data corresponding to any tissue type. The server is now capable of reordering the same compressed data file on the fly to serve data packets prioritized as per the client's request. Lastly, we describe the effect of compression parameters on compression ratio, decoding times and interactivity. We also present suggestions for optimizing JPEG2000 for remote volume visualization and volume browsing applications. The resulting system is ideally suited for client-server applications with the server maintaining the compressed volume data, to be browsed by a client with a low bandwidth constraint.",
keywords = "Code-block, Discrete wavelet transform (DWT), Embedded coding, JPEG2000, JPIP, Precinct, Scalable compression",
author = "Karthik Krishnan and Marcellin, {Michael W} and Ali Bilgin and Nadar, {Mariappan S.}",
year = "2006",
month = "9",
doi = "10.1109/TMI.2006.879956",
language = "English (US)",
volume = "25",
pages = "1189--1199",
journal = "IEEE Transactions on Medical Imaging",
issn = "0278-0062",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "9",

}

TY - JOUR

T1 - Efficient transmission of compressed data for remote volume visualization

AU - Krishnan, Karthik

AU - Marcellin, Michael W

AU - Bilgin, Ali

AU - Nadar, Mariappan S.

PY - 2006/9

Y1 - 2006/9

N2 - One of the goals of telemedicine is to enable remote visualization and browsing of medical volumes. There is a need to employ scalable compression schemes and efficient client-server models to obtain interactivity and an enhanced viewing experience. First, we present a scheme that uses JPEG2000 and JPIP (JPEG2000 Interactive Protocol) to transmit data in a multi-resolution and progressive fashion. The server exploits the spatial locality offered by the wavelet transform and packet indexing information to transmit, in so far as possible, compressed volume data relevant to the clients query. Once the client identifies its volume of interest (VOI), the volume is refined progressively within the VOI from an initial lossy to a final lossless representation. Contextual background information can also be made available having quality fading away from the VOI. Second, we present a prioritization that enables the client to progressively visualize scene content from a compressed file. In our specific example, the client is able to make requests to progressively receive data corresponding to any tissue type. The server is now capable of reordering the same compressed data file on the fly to serve data packets prioritized as per the client's request. Lastly, we describe the effect of compression parameters on compression ratio, decoding times and interactivity. We also present suggestions for optimizing JPEG2000 for remote volume visualization and volume browsing applications. The resulting system is ideally suited for client-server applications with the server maintaining the compressed volume data, to be browsed by a client with a low bandwidth constraint.

AB - One of the goals of telemedicine is to enable remote visualization and browsing of medical volumes. There is a need to employ scalable compression schemes and efficient client-server models to obtain interactivity and an enhanced viewing experience. First, we present a scheme that uses JPEG2000 and JPIP (JPEG2000 Interactive Protocol) to transmit data in a multi-resolution and progressive fashion. The server exploits the spatial locality offered by the wavelet transform and packet indexing information to transmit, in so far as possible, compressed volume data relevant to the clients query. Once the client identifies its volume of interest (VOI), the volume is refined progressively within the VOI from an initial lossy to a final lossless representation. Contextual background information can also be made available having quality fading away from the VOI. Second, we present a prioritization that enables the client to progressively visualize scene content from a compressed file. In our specific example, the client is able to make requests to progressively receive data corresponding to any tissue type. The server is now capable of reordering the same compressed data file on the fly to serve data packets prioritized as per the client's request. Lastly, we describe the effect of compression parameters on compression ratio, decoding times and interactivity. We also present suggestions for optimizing JPEG2000 for remote volume visualization and volume browsing applications. The resulting system is ideally suited for client-server applications with the server maintaining the compressed volume data, to be browsed by a client with a low bandwidth constraint.

KW - Code-block

KW - Discrete wavelet transform (DWT)

KW - Embedded coding

KW - JPEG2000

KW - JPIP

KW - Precinct

KW - Scalable compression

UR - http://www.scopus.com/inward/record.url?scp=33748124605&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33748124605&partnerID=8YFLogxK

U2 - 10.1109/TMI.2006.879956

DO - 10.1109/TMI.2006.879956

M3 - Article

VL - 25

SP - 1189

EP - 1199

JO - IEEE Transactions on Medical Imaging

JF - IEEE Transactions on Medical Imaging

SN - 0278-0062

IS - 9

M1 - 1677725

ER -