Neural network-assisted effective lossy compression of medical images

Author

Panagiotidis, Nikos G. ; Kalogeras, Dimitris ; Kollias, Stefanos D. ; Stafylopatis, Andreas

Author_Institution

Dept. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens, Greece

Volume

84

Issue

10

fYear

1996

fDate

10/1/1996 12:00:00 AM

Firstpage

1474

Lastpage

1487

Abstract

A neural network architecture is proposed and shown to be very effective in performing lossy compression of medical images. A novel ROI-JPEG technique is introduced as the coding platform, in which the neural architecture adaptively selects regions of interest (ROI) in the images. By letting the selected ROI be coded with high quality, in contrast to the rest of image areas, high compression ratios are achieved, while retaining the significant (from medical point of view) image content. The performance of the method is illustrated by means of experimental results in real life problems taken from pathology and telemedicine applications

Keywords

data compression; image coding; medical image processing; neural nets; JPEG; image coding; image compression; lossy compression; medical images; neural network architecture; pathology; regions of interest; telemedicine; Biomedical imaging; Image coding; Image quality; Image reconstruction; Magnetic resonance imaging; Mathematical model; Neural networks; Pathology; Solids; Telemedicine;

fLanguage

English

Journal_Title

Proceedings of the IEEE

Publisher

ieee

ISSN

0018-9219

Type

jour

DOI

10.1109/5.537112

Filename

537112