A modular software system to assist interpretation of medical images - Application to vascular ultrasound images

Stoitsis, J; Golemati, S; Nikita, KS

dc.contributor.author	Stoitsis, J	en
dc.contributor.author	Golemati, S	en
dc.contributor.author	Nikita, KS	en
dc.date.accessioned	2014-03-01T01:23:26Z
dc.date.available	2014-03-01T01:23:26Z
dc.date.issued	2006	en
dc.identifier.issn	0018-9456	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/16963
dc.subject	Computer-aided diagnosis (CAD)	en
dc.subject	Medical image analysis	en
dc.subject	Motion estimation	en
dc.subject	Texture analysis	en
dc.subject	Ultrasound imaging	en
dc.subject	Vascular disease	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.classification	Instruments & Instrumentation	en
dc.subject.other	Medical image analysis	en
dc.subject.other	Modular software system	en
dc.subject.other	Texture analysis	en
dc.subject.other	Vascular disease	en
dc.subject.other	Computer aided diagnosis	en
dc.subject.other	Computer software	en
dc.subject.other	Diseases	en
dc.subject.other	Feature extraction	en
dc.subject.other	Image analysis	en
dc.subject.other	Image quality	en
dc.subject.other	Motion estimation	en
dc.subject.other	Ultrasonic imaging	en
dc.subject.other	Medical imaging	en
dc.title	A modular software system to assist interpretation of medical images - Application to vascular ultrasound images	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/TIM.2006.884348	en
heal.identifier.secondary	http://dx.doi.org/10.1109/TIM.2006.884348	en
heal.language	English	en
heal.publicationDate	2006	en
heal.abstract	Improvements in medical imaging technology have greatly contributed to early disease detection and diagnosis. However, the accuracy of an examination depends on both the quality of the images and the ability of the physician to interpret those images. Use of output from computerized analysis of an image may facilitate the diagnostic tasks and, potentially improve the overall interpretation of images and the subsequent patient care. In this paper, ANALYSIS, a modular software system designed to assist interpretation of medical images, is described in detail. ANALYSIS allows texture and motion estimation of selected regions of interest (ROIs). Texture features can be estimated using first-order statistics, second-order statistics, Laws' texture energy, neighborhood gray-tone difference matrix, gray level difference statistics, and the fractal dimension. Motion can be estimated from temporal image sequences using block matching or optical flow. Image preprocessing, manual and automatic definition of ROIs, and dimensionality reduction and clustering using fuzzy c-means, are also possible within ANALYSIS. An important feature of ANALYSIS is the possibility for online telecollaboration between health care professionals under a secure framework. To demonstrate the applicability and usefulness of the system in clinical practice, ANALYSIS was applied to B-mode ultrasound images of the carotid artery. Diagnostic tasks included automatic segmentation of the arterial wall in transverse sections, selection of wall and plaque ROIs in longitudinal sections, estimation of texture features in different image areas, motion analysis of tissue ROIs, and clustering of the extracted features. It is concluded that ANALYSIS can provide a useful platform for computerized analysis of medical images and support of diagnosis. © 2006 IEEE.	en
heal.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
heal.journalName	IEEE Transactions on Instrumentation and Measurement	en
dc.identifier.doi	10.1109/TIM.2006.884348	en
dc.identifier.isi	ISI:000242948700011	en
dc.identifier.volume	55	en
dc.identifier.issue	6	en
dc.identifier.spage	1944	en
dc.identifier.epage	1952	en