Title
A 2-D Active Appearance Model For Prostate Segmentation In Ultrasound Images
Abstract
In this research we use an active appearance model (AAM) as the core of a robust segmentation algorithm that combines contour and texture information to learn shape variability through a training procedure in trans-rectal ultrasound (TRUS) images of the prostate. Training was carried out using a dataset of 95 images which are preprocessed using gray-level mathematical morphology operators. Preliminary results are promising. The segmentation can provide shapes that have an overlap with respect to a ground truth shape, traced by an expert, of up to 96%, and an average distance from point to curve of up to 1.3 pixels. © 2005 IEEE.
Publication Date
1-1-2005
Publication Title
Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume
7 VOLS
Number of Pages
3363-3366
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/iembs.2005.1617198
Copyright Status
Unknown
Socpus ID
33846919912 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/33846919912
STARS Citation
Medina, R.; Bravo, A.; and Windyga, P., "A 2-D Active Appearance Model For Prostate Segmentation In Ultrasound Images" (2005). Scopus Export 2000s. 4349.
https://stars.library.ucf.edu/scopus2000/4349