Automatic landmark annotation in 3D surface scans of skulls: Methodological proposal and reliability study

Dr. Bermejo's work has been supported by the Japan Society for the Promotion of Science (JSPS) as International Research Fellow (Standard Fellowship) . Dr. Mesejo's work is funded by the European Commission H2020-MSCA-IF-2016 through the Skeleton-ID Marie Curie Individ-ual Fellowship [Ref: 746592] . Dr. Valsecchi's work is funded by the Spanish Ministry of Sci-ence and Innovat19F19119ion grant [Ref: PTQ-17-09306] Drs. Ibanez work is funded by Spanish Ministry of Science, In-novation and Universities-CDTI, Neotec program 2019 [Ref: EXP-00122609/SNEO-20191236] . Additionally, This work was supported by the Grant-in-Aid for JSPS Fellows [Ref: 19F19119] , by the Spanish Ministry of Science, Innovation and Universities, and European Regional Development Funds (ERDF) , under grant EXASOCO [Ref: PGC2018-101216-B-I0 0] , and by the Regional Government of Andalusia under grant EXAISFI [Ref: P18-FR-4262] . Funding for open access publication was pro-vided by the University of Granada: CBUA.Background and Objectives: Craniometric landmarks are essential in many biomedical applications, such as morphometric analysis or forensic identification. The process of locating landmarks is usually a manual and slow task, highly influenced by fatigue, skills and the experience of the practitioner. Localization errors are propagated and magnified in subsequent steps, which can result in incorrect measurements or assumptions. Thereby, standardization, reliability and reproducibility lay the foundations for the necessary accuracy in subsequent measurements or anatomical analysis. In this paper, we present an automatic method to annotate 3D surface skull models taking into account anatomical and geometrical features. Methods: The proposed method follows a hybrid structure where a deformable template is used to initialize the landmark positions. Then, a refinement stage is applied using prior anatomical knowledge to ensure a correct placement. Our proposal is validated over thirty 3D skull scans of male Caucasians, acquired by hand-held surface scanning, and a set of 58 craniometric landmarks. A statistical analysis was carried out to analyze the inter-and intra-observer variability of manual annotations and the automatic results, along with a visual assessment of the final results. Results: Inter-observer errors show significant differences, which are reflected in the expert consensus used as reference. The average localization error was 2 . 19 +/- 1 . 5 mm when comparing the automatic landmarks to the reference location. The subsequent visual analysis confirmed the reliability of the refinement method for most landmarks. Conclusions: Repeated manual annotations show a high variability depending on both skills and expertise of the observer, and landmarks' location and characteristics. In contrast, the automatic method provides an accurate, robust and reproducible alternative to the tedious and error-prone task of manual landmarking.European CommissionEuropean Commission Joint Research Centre 746592Spanish Government PTQ-17-09306Spanish Ministry of Science, In-novation and Universities-CDTI, Neotec program 2019 EXP-00122609/SNEO-20191236Spanish Ministry of Science, Innovation and UniversitiesEuropean Regional Development Funds (ERDF) under grant EXASOCO PGC2018-101216-B-I0 0Regional Government of Andalusia under grant EXAISFI P18-FR-4262Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) Japan Society for the Promotion of Science19F1911

Forensic identification system using craniofacial superimposition based on soft computing

Número de publicación: ES2353099 B1. Número de solicitud: 200901732.Sistema de identificación forense por superposición craneofacial basado en soft computing. La presente invención viene dada por un método y un sistema automático que dan soporte al antropólogo forense en la tarea de identificación por superposición craneofacial. En primer lugar, el sistema construye de manera automática un modelo tridimensional a partir de un dispositivo que proporciona vistas parciales del cráneo. Posteriormente, se superpone dicho modelo sobre una fotografía de la persona desaparecida, modelando la incertidumbre inherente al emparejamiento de dos objetos distintos: un cráneo y una cara. Finalmente, el sistema emite una recomendación del resultado del proceso de identificación al antropólogo forense.This invention relates to a method and an automatic system for assisting a forensic anthropologist in the task of identification by means of craniofacial superimposition. First, the system automatically builds a three-dimensional model from a device providing partial views of the skull. Said model is then superimposed onto a photograph of the disappeared person, modelling the inherent uncertainty to the pairing of two separate objects: a skull and a face. Finally, the system emits a recommendation from the result of the identification process to the forensic anthropologist.Fundación para Progreso Soft ComputingUniversidad de Granad