Level set segmentation of bovine corpora lutea in ex situ ovarian ultrasound images
- PDF / 5,186,899 Bytes
- 16 Pages / 610 x 792 pts Page_size
- 42 Downloads / 173 Views
BioMed Central
Open Access
Research
Level set segmentation of bovine corpora lutea in ex situ ovarian ultrasound images Brennan J Rusnell1, Roger A Pierson2, Jaswant Singh3, Gregg P Adams3 and Mark G Eramian*1 Address: 1Department of Computer Science, University of Saskatchewan, Saskatoon, Saskatchewan, Canada, 2Department of Obstetrics, Gynecology and Reproductive Sciences, University of Saskatchewan, Saskatoon, Saskatchewan, Canada and 3Department of Veterinary Biomedical Sciences, University of Saskatchewan, Saskatoon, Saskatchewan, Canada Email: Brennan J Rusnell - [email protected]; Roger A Pierson - [email protected]; Jaswant Singh - [email protected]; Gregg P Adams - [email protected]; Mark G Eramian* - [email protected] * Corresponding author
Published: 4 August 2008 Reproductive Biology and Endocrinology 2008, 6:33
doi:10.1186/1477-7827-6-33
Received: 27 May 2008 Accepted: 4 August 2008
This article is available from: http://www.rbej.com/content/6/1/33 © 2008 Rusnell et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract Background: The objective of this study was to investigate the viability of level set image segmentation methods for the detection of corpora lutea (corpus luteum, CL) boundaries in ultrasonographic ovarian images. It was hypothesized that bovine CL boundaries could be located within 1–2 mm by a level set image segmentation methodology. Methods: Level set methods embed a 2D contour in a 3D surface and evolve that surface over time according to an image-dependent speed function. A speed function suitable for segmentation of CL's in ovarian ultrasound images was developed. An initial contour was manually placed and contour evolution was allowed to proceed until the rate of change of the area was sufficiently small. The method was tested on ovarian ultrasonographic images (n = 8) obtained ex situ. A expert in ovarian ultrasound interpretation delineated CL boundaries manually to serve as a "ground truth". Accuracy of the level set segmentation algorithm was determined by comparing semi-automatically determined contours with ground truth contours using the mean absolute difference (MAD), root mean squared difference (RMSD), Hausdorff distance (HD), sensitivity, and specificity metrics. Results and discussion: The mean MAD was 0.87 mm (sigma = 0.36 mm), RMSD was 1.1 mm (sigma = 0.47 mm), and HD was 3.4 mm (sigma = 2.0 mm) indicating that, on average, boundaries were accurate within 1–2 mm, however, deviations in excess of 3 mm from the ground truth were observed indicating under- or over-expansion of the contour. Mean sensitivity and specificity were 0.814 (sigma = 0.171) and 0.990 (sigma = 0.00786), respectively, indicating that CLs were consistently undersegmented but rarely did the contour interior inclu
Data Loading...
