Lossless volumetric colour medical image compression using block based encoding
by T. Kesavamurthy; K. Thiyagarajan
International Journal of Medical Engineering and Informatics (IJMEI), Vol. 4, No. 3, 2012

Abstract: Despite rapid improvements in storage and data transmission techniques, there is also an increasing need for medical image compression. The advancement in medical imaging systems such as computed tomography (CT), magnetic resonance imaging (MRI), positron emitted tomography (PET), and computed radiography (CR) produces huge amount of volumetric images about various anatomical structure of human body. There exists a need for compression of these images for storage and communication purposes. In this paper we proposed a lossless method of volumetric medical image compression and decompression using a block-based coding technique. The algorithm is tested for different sets of CT colour images using Matlab. The Digital Imaging and Communications in Medicine (DICOM) images are compressed using the proposed algorithm and stored as DICOM formatted images. The inverse nature of the algorithm is used to reconstruct the original image information loss lessly from the compressed DICOM files. We present the simulation results for large set of images to produce a comparative analysis between computational burden and compression ratio for various values of predefined block sizes. This paper finally proves the proposed methodology is better in terms of computational complexity and compression ratio.

Online publication date: Mon, 11-Aug-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Medical Engineering and Informatics (IJMEI):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com