Abstract #2882

Deterministic Automatic Segmentation in MRI, CT and CTA: A Robust Method Based on Anatomical Structures Modelling and Local Recursive Intensity Analysis

Manfredo Atzori^1,2, Gianluca Rambaldelli¹, Paolo Brambilla³, Alessandra Bertoldo²

¹Medicine and Public Health, Universit di Verona, Verona, Italy; ²Information Engineering, Universit di Padova, Padova, Italy; ³Pathology & Exp. Clin. Medicine, Universit di Udine, Udine, Italy

At the state of the art some semiautomatic and automatic segmentation procedures have been described. Current methods dont mind geometric and physical constitution of anatomical structures, not making a physically justified segmentation. This implies 8-9% volume errors, low methods concordance and low adaptability. We realized an automatic method for MRI, CT, CTA deterministic segmentation, based on mathematical modelling and analysis of anatomical structures physical and geometrical properties. It has been applied for several structures segmentation, as brain, grey-white matter, heart, kidneys, urinary tracts and bone. It is characterized by high precision (volume error 4.5%), non subjective parameters and high adaptability.