scholarly journals A pilot study of an automated personal identification process: Applying machine learning to panoramic radiographs

2021 ◽  
Vol 51 ◽  
Author(s):  
Adrielly Garcia Ortiz ◽  
Gustavo Hermes Soares ◽  
Gabriela Cauduro da Rosa ◽  
Maria Gabriela Haye Biazevic ◽  
Edgard Michel-Crosato
2019 ◽  
Vol 64 (6) ◽  
pp. 1796-1802 ◽  
Author(s):  
Annalisa Cappella ◽  
Daniele Gibelli ◽  
Zuzana Obertová ◽  
Marco Cummaudo ◽  
Elisa Castoldi ◽  
...  

Author(s):  
Andrea Palamenghi ◽  
Alessia Borlando ◽  
Danilo De Angelis ◽  
Chiarella Sforza ◽  
Cristina Cattaneo ◽  
...  

AbstractForensic anthropologists tasked with identification of skeletal remains often have to set up new strategies to overcome the limitations of conventional individualizing markers. A sound acquaintance with non-metric traits is essential for a reliable distinction between normal variations and pathological or traumatic conditions, yet the role of cranial variants in the identification process is still somehow ill-defined. One hundred crania (50 males and 50 females) of known sex and age were selected from the Collezione Antropologica LABANOF (a documented contemporary skeletal collection) and non-metric traits were scored as present or absent and by side. The frequencies of 13 traits were used to calculate the compound probabilities to find an individual with an exact combination of cranial features in the worldwide population. The probabilities of the majority of the individuals (53%) are within the 1 out of 10 million–1 out of 1 million interval. However, a fair number of subjects (25%) of the sample have the probabilities falling into the 1 out of 1 billion–1 out of 100 million interval, while the probabilities of a small portion of the sample (10%) are less than 1 out of 1 billion. This pilot study illustrates that some combinations of cranial variants are quite rare and may represent potential evidence to discern presumptive identifications, when an appropriate set of traits is selected and antemortem data are available for comparison. However, further research on larger and various samples is needed to confirm or discard the use of combinations of cranial non-metric traits as individualizing markers.


Author(s):  
Seungjun Ryu ◽  
Seunghyeok Back ◽  
Seongju Lee ◽  
Hyeon Seo ◽  
Chanki Park ◽  
...  

2020 ◽  
pp. 1-1
Author(s):  
Ekaterina Kovalenko ◽  
Aleksandr Talitckii ◽  
Anna Anikina ◽  
Aleksei Shcherbak ◽  
Olga Zimniakova ◽  
...  

2017 ◽  
Vol 7 (4) ◽  
Author(s):  
Vivek Velayudhan Nair ◽  
Sunila Thomas ◽  
Jincy Thomas ◽  
Cucoo Mariam Mathew

Osteoporosis characterized by low bone mass/osteopenia can be identified using radiomorphometric indices in routine panoramic radiographs. This study estimates the prevalence of osteopenia in 50-80 years age group, using panoramic mandibular index (PMI), mental index (MI) and mandibular cortical index (MCI). PMI, MI and MCI were applied on 36 panoramic radiographs; MI and MCI were compared with PMI. The prevalence of osteopenia was 11.1% with PMI and 44.4% with MCI. Using MI, the prevalence was 2.8% and 33.3% with 3mm and 4.77mm threshold respectively. The prevalence of osteopenia detected was highest using MCI (44.4%). Considering PMI as gold standard, MI with 4.77 mm threshold showed better agreement with PMI.


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