Segmentation of echo cardiographic image sequences using spatio-temporal information
1999 (English)In: Medical Image Computing and Computer-Assisted Intervention – MICCAI’99: Second International Conference, Cambridge, UK, September 19-22, 1999. Proceedings / [ed] Chris Taylor, Alan Colchester, Berlin: Springer, 1999, Vol. 1679, 410-419 p.Chapter in book (Refereed)
This paper describes a new method for improving border detection in image sequences by including both spatial and temporal information. The method is based on three dimensional quadrature filters for estimating local orientation. A simplification that gives a significant reduction in computational demand is also presented. The border detection framework is combined with a segmentation algorithm based on active contours or ’snakes’, implemented using a new optimization relaxation that can be solved to optimality using dynamical programming. The aim of the study was to compare segmentation performance using gradient based border detection and the proposed border detection algorithm using spatio-temporal information. Evaluation is performed both on a phantom and in-vivo data from five echocardiographic short axis image sequences. It could be concluded that when temporal information was included weak and incomplete boundaries could be found where gradient based border detection failed. Otherwise there was no significant difference in performance between the new proposed method and gradient based border detection.
Place, publisher, year, edition, pages
Berlin: Springer, 1999. Vol. 1679, 410-419 p.
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 1679
medical image computing, computer-assisted intervention, data-driven image segmentation, structural models, image processing, feature detection, surfaces, shape, measurement, image interpretation, spatiotemporal analysis, diffusion tensor analysis, image registration, data fusion, data visualisation, image-guided intervention, robotic systems, biomechanics, simulation
Medical and Health Sciences
IdentifiersURN: urn:nbn:se:liu:diva-49138DOI: 10.1007/10704282_45ISBN: 3-540-66503-XOAI: oai:DiVA.org:liu-49138DiVA: diva2:270034