A computational approach to estimate postmortem interval using opacity development of eye for human subjects
| Autor: | Lale Ozyilmaz, İsmail Cantürk |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Adult
Male Time Factors Opacity Databases Factual Margin of error Health Informatics Image processing Interval (mathematics) Eye 01 natural sciences Machine Learning 03 medical and health sciences 0302 clinical medicine Image Interpretation Computer-Assisted Humans 030216 legal & forensic medicine Forensic Pathology Aged business.industry 010401 analytical chemistry Pattern recognition Middle Aged 0104 chemical sciences Computer Science Applications Time of death Pmi estimation Postmortem Changes Female Artificial intelligence business |
| Zdroj: | Computers in biology and medicine. 98 |
| ISSN: | 1879-0534 |
| Popis: | This paper presents an approach to postmortem interval (PMI) estimation, which is a very debated and complicated area of forensic science. Most of the reported methods to determine PMI in the literature are not practical because of the need for skilled persons and significant amounts of time, and give unsatisfactory results. Additionally, the error margin of PMI estimation increases proportionally with elapsed time after death. It is crucial to develop practical PMI estimation methods for forensic science. In this study, a computational system is developed to determine the PMI of human subjects by investigating postmortem opacity development of the eye. Relevant features from the eye images were extracted using image processing techniques to reflect gradual opacity development. The features were then investigated to predict the time after death using machine learning methods. The experimental results prove that the development of opacity can be utilized as a practical computational tool to determine PMI for human subjects. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect