Sex determination on skeletal remains is one of the most important diagnosis in forensic cases and in demographic studies on ancient populations. Our purpose is to realize an automatic operator-independent method to determine the sex from the bone shape and to test an intelligent, automatic pattern recognition system in an anthropological domain. Our multiple-classifier system is based exclusively on the morphological variants of a curve that represents the sagittal profile of the calvarium, modeled via artificial neural networks, and yields an accuracy higher than 80 %. The application of this system to other bone profiles is expected to further improve the sensibility of the methodology.
|Titolo:||Use of pattern recognition and neural networks for non-metric sex diagnosis from lateral shape of calvarium: an innovative model for computer-aided diagnosis in forensic and physical anthropology|
|Rivista:||INTERNATIONAL JOURNAL OF LEGAL MEDICINE|
|Citazione:||Cavalli, F., Lusnig, L., & Trentin, E. (2017). Use of pattern recognition and neural networks for non-metric sex diagnosis from lateral shape of calvarium: an innovative model for computer-aided diagnosis in forensic and physical anthropology. INTERNATIONAL JOURNAL OF LEGAL MEDICINE, 131(3), 823-833.|
|Appare nelle tipologie:||1.1 Articolo in rivista|