Call: H2020-MSCA-IF-2016 (Marie Skłodowska-Curie Individual Fellowships).
Type of action: MSCA-IF-EF-ST (Standard European Fellowship)
Proposal number: 746592
Proposal acronym: SKELETON-ID
Budget: 170.121,6€
Duration: April 2018 - May 2020
Funding Institution: European Commission
List of Participants:
- Experienced Researcher/Principal Investigator: Dr. Pablo Mesejo
- Beneficiary Institution (UGR-SOCCER) Supervisor: Dr. Óscar Cordón
- Academic Partner Institution (UGR-PAL) Supervisor: Dr. Inmaculada Alemán
- Industrial Partner Institution (PANACEA) Supervisor: Dr. Óscar Ibáñez
Success Rate: 13.10% in the H2020-MSCA-IF-2016 call
Keywords: Artificial intelligence; Intelligent systems; Computer vision; Machine learning; Physical anthropology; Forensic anthropology; Forensic radiology; Forensic identification; Skeleton-based identification
Forensic human identification is a great challenge in the preservation and defense of Human Rights. There is an urgent need to provide forensic practitioners with accurate, robust, unbiased and automatic identification systems. The MSCA IF 'Skeleton-ID' fills this technological gap by bringing a novel artificial intelligence-based automatic paradigm for human identification using a forensic anthropology approach called comparative radiography (CR).
CR traditionally involves the use of antemortem (AM) radiographs of the suspected deceased, producing postmortem (PM) radiographs that simulate the AM ones in scope and projection, and then performing a comparison looking for consistencies and inconsistencies in bone morphology, pathological and trauma conditions, etc. CR requires a prior record of clinical images that are not always available; but if present, this technique is extremely accurate, reaching >99% reliability for certain bones. Despite their proven validity for identification purposes more than 50 years ago, automatic and objective approaches are in their infancy in this field. Most existing proposals rely on the expert's skills and experience and follow an error-prone, time-consuming and subjective approach requiring PM X-ray acquisition in the same conditions of the AM one, and the manual delineation of the bone in AM and PM radiographies.
Skeleton-ID includes 5 Work Packages (WPs): Bone segmentation in radiographic images (WP1); Study, design, and implementation of a computer-aided automatic CR ID system (WP2); Machine learning in biological profiling, and multi-evidence fusion (WP3); Training, Supervision and Project Management (WP4); and Dissemination & Exploitation (WP5). Ultimately, the complete automatic CR system to be developed is composed of three stages:
i) image segmentation: automatic delineation of the target bone's contour in the AM radiography;
ii) image registration: automatic comparison of the PM 3D model of the bone and the delineated AM radiography;
iii) computer-aided decision support system able to integrate all available information and to assist the forensic expert in the decision making process.
Gómez, Ó., Mesejo, P., Ibáñez, Ó., and Cordón, Ó., "Deep architectures for the segmentation of frontal sinuses in X-Ray images: towards an automatic forensic identification system in comparative radiography", submitted to Neurocomputing, Special Issue on "Hybrid Artificial Intelligent Systems", Elsevier, 2020 (IF2018: 4.072 (Q1), 28th/134 in subject category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
Mesejo, P., Martos, R., Ibáñez, Ó., Novo, J., and Ortega, M., "A Survey on Artificial Intelligence Techniques for Biomedical Image Analysis in Skeleton-based Forensic Human Identification", submitted to Applied Sciences, Special Issue on "Computer-aided Biomedical Imaging 2020: Advances and Prospects", Multidisciplinary Digital Publishing Institute, 2020 (IF2018: 2.217 (Q2), 67th/148 in subject category PHYSICS, APPLIED; Q3, 89th/172 in subject category CHEMISTRY, MULTIDISCIPLINARY; Q3, 151st/293 in subject category MATERIALS SCIENCES, MULTIDISCIPLINARY)
Gómez, Ó., Mesejo, P., Ibáñez, Ó., Valsecchi, A., and Cordón, Ó., “Deep architectures for high-resolution multi-organ chest X-ray image segmentation”, Neural Computing & Applications, Special Issue on "Recent Advances in Deep Learning for Medical Image Processing and Health Informatics", In Press, Springer, October - 2019 (IF2018: 4.664 (Q1), 21st/133 in subject category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
Valsecchi, A., Irurita, J., and Mesejo, P., “Age estimation in forensic anthropology: methodological considerations about the validation studies of prediction models”, International Journal of Legal Medicine 133, 1915-1924, Springer, May - 2019 (IF2018: 2.094 (Q1), 4th/17 in subject category MEDICINE, LEGAL)
Mesejo, P., "Soft computing and computer vision for comparative radiography in forensic identification", dissemination article at The Project Repository Journal 5, 12-15, April-2020
Ibáñez, Ó., Martos, R., and Mesejo, P., "Inteligencia Artificial en Antropología Forense: estado del arte, retos y oportunidades", submitted to Revista de la Asociación Española de Antropología y Odontología Forense, In Press, 2020
Martos, R., Ibáñez, Ó., and Mesejo, P., "Artificial Intelligence in Forensic Anthropology: state of the art and Skeleton-ID project", submitted to Methodological and Technological Advances in Forensic Science: Application and Case Studies, Edited by Ann H. Ross and Jason Byrd, In Press, 2020
Gómez, Ó., Mesejo, P., Ibáñez, Ó., Valsecchi, A., and Cordón, Ó., "A real-coded evolutionary algorithm-based registration approach for forensic identification using the radiographic comparison of frontal sinuses", 22nd IEEE Congress on Evolutionary Computation (IEEE CEC’20), Glasgow, July-2020 (CORE2018 B, GGS rating A-)
Gómez, Ó., Mesejo, P., Ibáñez, Ó., Valsecchi, A., Cerezo, A., Pérez, J.M., Alemán, I., and Cordón, Ó., "Automatic segmentation of skeletal structures in X-ray images using deep learning for comparative radiography", accepted for presentation at the 9th Annual Congress of the International Society of Forensic Radiology and Imaging (ISFRI'20), Albuquerque (USA), May 14-16, 2020. Canceled due to COVID-19.
Gómez, Ó., Ibáñez, Ó., Mesejo, P., Valsecchi, A., Cerezo, A., Pérez, J.M., Alemán, I., and Cordón, Ó., "Towards a computer-aided decision support system for comparative radiography", accepted for presentation at the 9th Annual Congress of the International Society of Forensic Radiology and Imaging (ISFRI'20), Albuquerque (USA), May 14-16, 2020. Canceled due to COVID-19.
Ibáñez, Ó., Corbal, I., Gómez, I., Gómez, Ó., González, A., Macías, M., Prada, K., Valsecchi, A., and Mesejo, P., "Skeleton-ID: Artificial Intelligence at the service of Forensic Anthropology", accepted for presentation at the 11th International Scientific Meeting of the Spanish Association of Forensic Anthropology and Odontology (AEAOF'19), Pastrana (Spain), November 8-9, 2019
Gómez, Ó., Ibáñez, Ó., Mesejo, P., Valsecchi, A., and Cordón, Ó., “Towards a computer-aided decision support system for comparative radiography”, accepted for presentation at the 11th International Scientific Meeting of the Spanish Association of Forensic Anthropology and Odontology (AEAOF'19), Pastrana (Spain), November 8-9, 2019
Gómez, G., Mesejo, P., Ibáñez, Ó., Valsecchi, A., and Cordón, Ó., "Automatic localization of cephalometric landmarks using convolutional networks", accepted for presentation at the 11th International Scientific Meeting of the Spanish Association of Forensic Anthropology and Odontology (AEAOF'19), Pastrana (Spain), November 8-9, 2019
Irurita, J., Valsecchi, A., Mesejo, P., and Alemán, I., “Improvement of a method for estimating dental age in children through the use of learning algorithms”, accepted for presentation at the 21st Congress of the Spanish Society of Physical Anthropology (SEAF'19), Granada, June 24-26, 2019
Fernández, E., Valsecchi, A., Ibáñez, Ó., and Mesejo, P., “Estimating subject-to-camera distance in facial images using Deep Learning”, accepted for a podium presentation at the 18th Biennial Meeting of the International Association of Craniofacial Identification (IACI'19) July 13-17, 2019 in Baton Rouge, Louisiana, USA. Canceled due to Tropical Storm Threat, and re-organized then as "IACI 2019 Online Symposium".
Gómez, Ó., Mesejo, P., Ibáñez, Ó., Valsecchi, A., and Cordón, Ó., “Automatic segmentation of skeletal structures in x-ray images using deep learning: Towards a computer-aided decision support system for comparative radiography”, accepted for a podium presentation at the 18th Biennial Meeting of the International Association of Craniofacial Identification (IACI'19) July 13-17, 2019 in Baton Rouge, Louisiana, USA. Canceled due to Tropical Storm Threat, and re-organized then as "IACI 2019 Online Symposium".
Urdín, D., Mesejo, P., Ibáñez, Ó., Valsecchi, A., Guyomarc'h, P., and Coqueugniot, H., “Facial Soft Tissue Depth Estimation using Machine Learning Techniques”, accepted for a podium presentation at the 18th Biennial Meeting of the International Association of Craniofacial Identification (IACI'19) July 13-17, 2019 in Baton Rouge, Louisiana, USA. Canceled due to Tropical Storm Threat, and re-organized then as "IACI 2019 Online Symposium".
Gómez, G., Mesejo, P., Ibáñez, Ó., and Valsecchi, A., “Automatic Cephalometric Landmarks Localization using Deep Convolutional Neural Networks”, accepted for a poster presentation at the 18th Biennial Meeting of the International Association of Craniofacial Identification (IACI'19) July 13-17, 2019 in Baton Rouge, Louisiana, USA. Canceled due to Tropical Storm Threat, and re-organized then as "IACI 2019 Online Symposium".
Co-founder, partner and R&D co-director of Panacea Cooperative Research (an SME focused on finding intelligent solutions to solve unmet biomedical needs):
https://www.panacea-coop.com/index.php/en/ Panacea is a UGR spin-off and member of the Data Science and Computational Intelligence Innovation Hub (DaSCII Hub). It was founded in August 2017, and started its economic activity in the second trimester of 2018. First product: Skeleton-ID (https://skeleton-id.com/).
Patent of invention application: "Identification Procedure of Osseous Images" ("Procedimiento de identificación de imágenes óseas"). Inventors: Óscar David Gómez López; Óscar Ibáñez Panizo; Pablo Mesejo Santiago; Óscar Cordón García; Sergio Damas Arroyo; Andrea Valsecchi. Universidad de Granada. Number of application: P201831303. Country of inscription: Spain, Andalusia. Registration Date: 29/12/2018. PCT number application: PCT/ES2019/070887. PCT application date: 26/12/2019.
Patent of invention application: "Image Analysis System for Forensic Facial Comparion" ("Sistema de análisis de imágenes para la comparación facial forense"). Inventors: Rubén Martos Fernández; Óscar Ibáñez Panizo; Andrea Valsecchi; Pablo Mesejo Santiago; Alexsandro Vasconcellos da Silva; Fernando Navarro Merino; Inmaculada Alemán Aguilera; Óscar Cordón García; Sergio Damas Arroyo. Universidad de Granada & Panacea Cooperative Research. Number of application: P202030191. Country of inscription: Spain, Andalusia. Registration Date: 06/03/2020.
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