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.
authors.affiliation: Universidad de Los Andes, Grupo de Ingenier&#237;a Biom&#233;dica (GIBULA) M&#233;rida 5101, Venezuela. Email: rmedina@ula.ve.
authors.forename: R
authors.initials: R
authors.lastname: Medina
authors.forename: A
authors.initials: A
authors.lastname: Bravo
authors.forename: P
authors.initials: P
authors.lastname: Windyga
authors.forename: J
authors.initials: J
authors.lastname: Toro
authors.forename: P
authors.initials: P
authors.lastname: Yan
authors.forename: G
authors.initials: G
authors.lastname: Onik