Validation and Development of a New Automatic Algorithm for Time-Resolved Segmentation of the Left Ventricle in Magnetic Resonance Imaging.
Tufvesson, Jane LU ; Hedström, Erik LU
; Steding Ehrenborg, Katarina
LU
; Carlsson, Marcus
LU
; Arheden, Håkan
LU
and Heiberg, Einar
LU
(2015)
In BioMed Research International
2015.
- Abstract
- Introduction. Manual delineation of the left ventricle is clinical standard for quantification of cardiovascular magnetic resonance images despite being time consuming and observer dependent. Previous automatic methods generally do not account for one major contributor to stroke volume, the long-axis motion. Therefore, the aim of this study was to develop and validate an automatic algorithm for time-resolved segmentation covering the whole left ventricle, including basal slices affected by long-axis motion. Methods. Ninety subjects imaged with a cine balanced steady state free precession sequence were included in the study (training set n = 40, test set n = 50). Manual delineation was reference standard and second observer analysis was... (More)
- Introduction. Manual delineation of the left ventricle is clinical standard for quantification of cardiovascular magnetic resonance images despite being time consuming and observer dependent. Previous automatic methods generally do not account for one major contributor to stroke volume, the long-axis motion. Therefore, the aim of this study was to develop and validate an automatic algorithm for time-resolved segmentation covering the whole left ventricle, including basal slices affected by long-axis motion. Methods. Ninety subjects imaged with a cine balanced steady state free precession sequence were included in the study (training set n = 40, test set n = 50). Manual delineation was reference standard and second observer analysis was performed in a subset (n = 25). The automatic algorithm uses deformable model with expectation-maximization, followed by automatic removal of papillary muscles and detection of the outflow tract. Results. The mean differences between automatic segmentation and manual delineation were EDV -11 mL, ESV 1 mL, EF -3%, and LVM 4 g in the test set. Conclusions. The automatic LV segmentation algorithm reached accuracy comparable to interobserver for manual delineation, thereby bringing automatic segmentation one step closer to clinical routine. The algorithm and all images with manual delineations are available for benchmarking. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/7749364
- author
- Tufvesson, Jane
LU
; Hedström, Erik
LU
; Steding Ehrenborg, Katarina
LU
; Carlsson, Marcus
LU
; Arheden, Håkan
LU
and Heiberg, Einar
LU
- organization
- publishing date
- 2015
- type
- Contribution to journal
- publication status
- published
- subject
- in
- BioMed Research International
- volume
- 2015
- article number
- 970357
- publisher
- John Wiley & Sons Inc.
- external identifiers
-
- pmid:26180818
- wos:000357468600001
- scopus:84936767063
- pmid:26180818
- ISSN
- 2314-6133
- DOI
- 10.1155/2015/970357
- language
- English
- LU publication?
- yes
- id
- f3ac812e-4462-4cfe-985b-03c814e623a5 (old id 7749364)
- alternative location
- http://www.ncbi.nlm.nih.gov/pubmed/26180818?dopt=Abstract
- date added to LUP
- 2016-04-01 10:08:07
- date last changed
- 2025-04-04 13:59:42
@article{f3ac812e-4462-4cfe-985b-03c814e623a5,
abstract = {{Introduction. Manual delineation of the left ventricle is clinical standard for quantification of cardiovascular magnetic resonance images despite being time consuming and observer dependent. Previous automatic methods generally do not account for one major contributor to stroke volume, the long-axis motion. Therefore, the aim of this study was to develop and validate an automatic algorithm for time-resolved segmentation covering the whole left ventricle, including basal slices affected by long-axis motion. Methods. Ninety subjects imaged with a cine balanced steady state free precession sequence were included in the study (training set n = 40, test set n = 50). Manual delineation was reference standard and second observer analysis was performed in a subset (n = 25). The automatic algorithm uses deformable model with expectation-maximization, followed by automatic removal of papillary muscles and detection of the outflow tract. Results. The mean differences between automatic segmentation and manual delineation were EDV -11 mL, ESV 1 mL, EF -3%, and LVM 4 g in the test set. Conclusions. The automatic LV segmentation algorithm reached accuracy comparable to interobserver for manual delineation, thereby bringing automatic segmentation one step closer to clinical routine. The algorithm and all images with manual delineations are available for benchmarking.}},
author = {{Tufvesson, Jane and Hedström, Erik and Steding Ehrenborg, Katarina and Carlsson, Marcus and Arheden, Håkan and Heiberg, Einar}},
issn = {{2314-6133}},
language = {{eng}},
publisher = {{John Wiley & Sons Inc.}},
series = {{BioMed Research International}},
title = {{Validation and Development of a New Automatic Algorithm for Time-Resolved Segmentation of the Left Ventricle in Magnetic Resonance Imaging.}},
url = {{http://dx.doi.org/10.1155/2015/970357}},
doi = {{10.1155/2015/970357}},
volume = {{2015}},
year = {{2015}},
}