Segmentation of echocardiographic image sequences using spatio-temporal information
Brandt, Einar LU
; Wigström, Lars
and Wranne, Bengt
(1999)
2nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 1999
In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
1679.
p.410-419
- Abstract
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... (More)
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.
(Less)
- author
- Brandt, Einar
LU
; Wigström, Lars
and Wranne, Bengt
- publishing date
- 1999
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- host publication
- Medical Image Computing and Computer-Assisted Intervention –MICCAI 1999 - 2nd International Conference, Proceedings
- series title
- Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
- editor
- Taylor, Chris and Colchester, Alain
- volume
- 1679
- pages
- 410 - 419
- publisher
- Springer
- conference name
- 2nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 1999
- conference location
- Cambridge, United Kingdom
- conference dates
- 1999-09-19 - 1999-09-22
- external identifiers
-
- scopus:84957078728
- ISSN
- 0302-9743
- 1611-3349
- ISBN
- 354066503X
- 9783540665038
- DOI
- 10.1007/10704282_45
- language
- English
- LU publication?
- no
- additional info
- Publisher Copyright: © Springer-Verlag Berlin Heidelberg 1999.
- id
- 7905de18-eb21-4a68-9288-3fd305aa4241
- date added to LUP
- 2022-10-21 10:25:49
- date last changed
- 2025-04-19 02:15:19
@inproceedings{7905de18-eb21-4a68-9288-3fd305aa4241,
abstract = {{<p>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.</p>}},
author = {{Brandt, Einar and Wigström, Lars and Wranne, Bengt}},
booktitle = {{Medical Image Computing and Computer-Assisted Intervention –MICCAI 1999 - 2nd International Conference, Proceedings}},
editor = {{Taylor, Chris and Colchester, Alain}},
isbn = {{354066503X}},
issn = {{0302-9743}},
language = {{eng}},
pages = {{410--419}},
publisher = {{Springer}},
series = {{Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}},
title = {{Segmentation of echocardiographic image sequences using spatio-temporal information}},
url = {{http://dx.doi.org/10.1007/10704282_45}},
doi = {{10.1007/10704282_45}},
volume = {{1679}},
year = {{1999}},
}