Neural network-assisted effective lossy compression of medical images

Panagiotidis, NG; Kalogeras, D; Kollias, SD; Stafylopatis, A

dc.contributor.author	Panagiotidis, NG	en
dc.contributor.author	Kalogeras, D	en
dc.contributor.author	Kollias, SD	en
dc.contributor.author	Stafylopatis, A	en
dc.date.accessioned	2014-03-01T01:12:07Z
dc.date.available	2014-03-01T01:12:07Z
dc.date.issued	1996	en
dc.identifier.issn	0018-9219	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/11957
dc.subject	Compression Ratio	en
dc.subject	Lossy Compression	en
dc.subject	Medical Image	en
dc.subject	Point of View	en
dc.subject	Neural Network	en
dc.subject	Region of Interest	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.title	Neural network-assisted effective lossy compression of medical images	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/5.537112	en
heal.identifier.secondary	http://dx.doi.org/10.1109/5.537112	en
heal.language	English	en
heal.publicationDate	1996	en
heal.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 adoptively selects regions of interest (ROI's) in the images. By letting the selected ROI's 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. © 1996 IEEE.	en
heal.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
heal.journalName	Proceedings of the IEEE	en
dc.identifier.doi	10.1109/5.537112	en
dc.identifier.isi	ISI:A1996VK62400009	en
dc.identifier.volume	84	en
dc.identifier.issue	10	en
dc.identifier.spage	1474	en
dc.identifier.epage	1487	en