A Survey on Artificial Intelligence Techniques for Biomedical Image Analysis in Skeleton-Based Forensic Human Identification Mesejo Santiago, Pablo Martos, Rubén Ibáñez, Óscar Novo, Jorge Ortega, Marcos Forensic medicine Forensic anthropology Forensic imaging Skeleton-based forensic identification Machine learning Computer vision Soft computing Biological profiling Comparative radiography Craniofacial identification This paper represents the first survey on the application of AI techniques for the analysis of biomedical images with forensic human identification purposes. Human identification is of great relevance in today’s society and, in particular, in medico-legal contexts. As consequence, all technological advances that are introduced in this field can contribute to the increasing necessity for accurate and robust tools that allow for establishing and verifying human identity. We first describe the importance and applicability of forensic anthropology in many identification scenarios. Later, we present the main trends related to the application of computer vision, machine learning and soft computing techniques to the estimation of the biological profile, the identification through comparative radiography and craniofacial superimposition, traumatism and pathology analysis, as well as facial reconstruction. The potentialities and limitations of the employed approaches are described, and we conclude with a discussion about methodological issues and future research. 2020-09-10T10:41:03Z 2020-09-10T10:41:03Z 2020-07-08 info:eu-repo/semantics/article Mesejo, P., Martos, R., Ibáñez, Ó., Novo, J., & Ortega, M. (2020). A Survey on Artificial Intelligence Techniques for Biomedical Image Analysis in Skeleton-Based Forensic Human Identification. Applied Sciences, 10(14), 4703. [doi: 10.3390/app10144703] http://hdl.handle.net/10481/63371 10.3390/app10144703 eng http://creativecommons.org/licenses/by/3.0/es/ info:eu-repo/semantics/openAccess Atribución 3.0 España MDPI