Reversible compression techniques for high-resolution digital teleradiology

Gopinath R. Kuduvalli; Rangaraj M. Rangayyan

doi:10.1117/12.23865

1 June 1990 Reversible compression techniques for high-resolution digital teleradiology

Gopinath R. Kuduvalli, Rangaraj M. Rangayyan

Proceedings Volume 1355, Telecommunication for Health Care: Telemetry, Teleradiology, and Telemedicine; (1990) https://doi.org/10.1117/12.23865
Event: Telecommunication for Health Care: Telemetry, Teleradiology, and Telemedicine, 1990, Calgary, Canada

Abstract

The sheer amount of data involved in the fields of Picture Archival and Communication systems (PACS) and Teleradiology has created a growing interest in efficient compression of medical images. Diagnostic quality digitization of typical medical images such as chest x-rays and mammograms requires about 4Kx4K pixels digitized to 10 or 12 bits. In most medical applications any loss of quality in compression and decompression of images cannot be tolerated. We are investigating coding techniques for reversible compression of medical images in the above context. In this paper we present the results of application of adaptive linear predictive coding techniques to a few typical medical images digitized to about 4Kx4Kxl2-bits using an Eikonix 1412 camera. It was seen that about 75 reduction in transmission times is possible without any loss of image quality for the images considered. It was observed that the optimal predictor order and the optimal block size for adaptive linear predictive coding are higher compared to those for the same images digitized to lower spatial resolution. 1.

Citation Download Citation

Gopinath R. Kuduvalli and Rangaraj M. Rangayyan "Reversible compression techniques for high-resolution digital teleradiology", Proc. SPIE 1355, Telecommunication for Health Care: Telemetry, Teleradiology, and Telemedicine, (1 June 1990); https://doi.org/10.1117/12.23865

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available