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

Socpus ID

33846919912 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/33846919912

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