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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.

SUMMARY This paper describes a block silver impregnation technique for the CNS. The procedure, which is quite simple, yields highly consistent and reproducible results. After fixation during 6–10 days in 10% saline formaldehyde, 4 mm thick blocks of brain are treated with chromic anhydride and sodium potassium tartrate solution for 4 days. After this period the specimens are rinsed in 0.75% silver nitrate solution to which 8–10 drops of pyridine per 100 ml of solution have been added. This is followed by impregnation for 4 days at 37°C in silver nitrate‐pyridine solution identical to that used in the previous rinsing step. The impregnated blocks are reduced during 20–26 h in 1% pyrogallol to which 6 ml commercial formaldehyde per 100 ml of solution have been added, followed by dehydration in dioxan and paraffin embedding. Sections no thicker than 30 μm are then cut for histological study. This fundamentally neurofibrillar method reveals: (a) neuronal somata and their processes; (b) synaptic structures; (c) fibre bundles; and (d) cell nuclei and nucleoli.

In 2017, a series of human remains corresponding to the executed leaders of the “January Uprising” of 1863–1864 were uncovered at the Upper Castle of Vilnius (Lithuania). During the archeological excavations, 14 inhumation pits with the human remains of 21 individuals were found at the site. The subsequent identification process was carried out, including the analysis and cross-comparison of post-mortem data obtained in situ and in the lab with ante-mortem data obtained from historical archives. In parallel, three anthropologists with diverse backgrounds in craniofacial identification and two students without previous experience attempted to identify 11 of these 21 individuals using the craniofacial superimposition technique. To do this, the five participants had access to 18 3D scanned skulls and 14 photographs of 11 different candidates. The participants faced a cross-comparison problem involving 252 skull-face overlay scenarios. The methodology follows the main agreements of the European project MEPROCS and uses the software Skeleton-ID™. Based on MEPROCS standard, a final decision was provided within a scale, assigning a value in terms of strong, moderate, or limited support to the claim that the skull and the facial image belonged (or not) to the same person for each case. The problem of binary classification, positive/negative, with an identification rate for each participant was revealed. The results obtained in this study make the authors think that both the quality of the materials used and the previous experience of the analyst play a fundamental role when reaching conclusions using the CFS technique.