A 2-d active appearance model for prostate segmentation in ultrasound images.
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.
Medina
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R
Universidad de Los Andes, Grupo de Ingenier&#237;a Biom&#233;dica (GIBULA) M&#233;rida 5101, Venezuela. Email: rmedina@ula.ve.
Bravo
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Windyga
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Toro
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Yan
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Onik
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