Skip to main navigation Skip to search Skip to main content

Wavelet-based compression of pathological images for telemedicine applications

  • University of Missouri

Research output: Contribution to journal › Conference article › peer-review

3 Scopus citations

Abstract

In this paper, we present the performance evaluation of wavelet-based coding techniques as applied to the compression of pathological images for application in an Internet-based telemedicine system. We first study how well suited the wavelet-based coding is as it applies to the compression of pathological images, since these images often contain fine textures that are often critical to the diagnosis of potential diseases. We compare the wavelet-based compression with the DCT-based JPEG compression in the DICOM standard for medical imaging applications. Both objective and subjective measures have been studied in the evaluation of compression performance. These studies are performed in close collaboration with expert pathologists who have conducted the evaluation of the compressed pathological images and communication engineers and information scientists who designed the proposed telemedicine system. These performance evaluations have shown that the wavelet-based coding is suitable for the compression of various pathological images and can be integrated well with the Internet-based telemedicine systems. A prototype of the proposed telemedicine system has been developed in which the wavelet-based coding is adopted for the compression to achieve bandwidth efficient transmission and therefore speed up the communications between the remote terminal and the central server of the telemedicine system.

Original languageEnglish
Pages (from-to)113-122
Number of pages10
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume3980
StatePublished - 2000
EventMedical Imaging 2000 - PACS Design and Evaluation: Engineering and Clinical Issues - San Diego, CA, USA
Duration: Feb 15 2000 → Feb 17 2000

Fingerprint

Dive into the research topics of 'Wavelet-based compression of pathological images for telemedicine applications'. Together they form a unique fingerprint.

Cite this