Expectations and Difficulties of Personal Identification Using Advanced Digital Imaging and Radiological Technology

Mismihra Yoko^*
*Correspondence: Mismihra Yoko, Department of Forensic Pathology and Sciences, Kyushu University, Fukuoka, Japan, Email:

Keywords

Personal identification • Biological fingerprints • Mass disaster • Digital radiography

Introduction

Forensic anthropology has employed human remains or bones from a deceased individual to analyse human remains for more than a century. It is common knowledge that DNA testing, fingerprinting, and dental records are reliable ways to gather enough proof to identify people who have passed away or victims of natural disasters. Bone information is also used by several forensic anthropologists, forensic pathologists, and radiological technology researchers to determine age and sex. To apply to unsolved cases and human remains, medical examiners/coroners, forensic pathologists, and forensic anthropologists are constantly developing standards and methodical analysis techniques. Creating a quick and accurate identification technique for use by a small group of professionals on-site following an unforeseen mass disaster occurrence is one strategy to improve forensic personal identification. The challenge of identifying a catastrophe victim by visual recognition was acknowledged by Interpol when it published standards for Disaster Victim Identification (DVI) in 2000. Since 2008, the Organization of Scientific Area Committees for Forensic Science and the Scientific Working Group for Forensic Anthropology have collaborated to organise, establish best practises for, and develop a consensus standard [1].

The Act of Promotion of Policy about Death Investigation was passed into law in April 2020 as a result of the Japanese government's creation of "The Program on Promotion of Policy about Death Investigation" in June 2014. This program's objectives include using scientific techniques to determine the cause of death, establishing procedures for dental records, and creating databases for the identification of the deceased. When the subsequent major catastrophe will occur is impossible to predict. Identification of victims is delayed as a result of inadequate planning for upcoming major catastrophes. Before the next major calamity strikes, researchers have been carefully debating and researching how to work with police officers and coroners. This is crucial, particularly during terrorism-related incidents, earthquakes, tsunamis, floods, and wildfires. This article outlines the difficulties with personal identification as well as the cuttingedge technology being created for radiography permission and identification. A new review that concentrated on radiographic technology and medical physics is available with detailed summaries. The objective of this review is to present information and viewpoints on the creation of efficient and practical procedures for forensic pathology and anthropology [2-4].

Literature Review

Recent imaging technologies in medically developed nations have evolved to be totally digital since the creation of computed radiography, the first successful digital radiographic instrument, in 1983. This modification enables us to reconsider numerous effective approaches that have been created in forensic pathology and anthropology.

In hospitals and medical facilities, people who reside in medically advanced nations may have their own images or may bring in their own images as recorded media. Except for retrospective investigations by a small group of scholars, these photos cannot be accessed without special authorization and cannot be reused. Moreover, with the exception of clinically noteworthy or rare situations, these photographs may be erased after a specific retention period as established by national or state law. Researchers need to be mindful of victims' or patients' privacy. On the other hand, guidelines for upcoming major catastrophes should be discussed, and relevant societies and associations should work with coroners to coordinate response efforts. Digitally obtained photos that have been structured well, such as those in the Digital Imaging and Communications in Medicine (DICOM) format, can be easily disseminated globally.

Discussion

Researchers from all over the world require a variety of picture databases in order to do DVI after an unforeseen mass calamity. Apart from fingerprint and DNA analyses, positive identification would be one of the most efficient ways to identify victims of a major disaster if researchers could access databases that contained antemortem data. For victims of a fire or tsunami, for instance, it is challenging to match the body and appearance. Unfortunately, open national databases do not exist due to security and ethical concerns, with the exception of a few local databases. Due to patient privacy, digital photographs, clinical data, and reports that are already available in hospitals or medical facilities are also inaccessible. Using data from a patient's medical records is confidential, yet it needs to be structured in a digital database so that it may be made accessible online in an emergency.

To ascertain the cause of death and to compare pictures for the purpose of identifying people based on anatomical information, PMCT scans should ideally match antemortem CT scans. In some circumstances, repositioning is necessary when the anatomical location between the PMCT and AMCT has been moved. The cadaver bag and posthumous rigidity affect how frequently it is used. An anthropological basal line can be used as another potential relocation strategy. If such automation and correction were implemented in CT machines, it would improve the repeatability of the imaging and allow for the determination of the cause of death by PMCT without having any negative effects on the deceased [5,6].

Conclusion

Precision estimation is made possible by AI by the rapid examination of numerous chosen features, which is unmatched by manual methods. Numerous disciplines are quickly adopting AI research, and it has already begun to be applied in medicine. However, it is unknown how resilient or beneficial it might be. An AI system can be created using a mathematically sound model for a particular topic and trained with a large enough sample size. It is anticipated that the usage of AI will increase and support forensic pathologists in their estimation of a deceased person's time of death, cause of death, age, and sexual orientation. However, prior to usage, consensus and consistent agreements with knowledgeable forensic pathologists are required. To increase the likelihood of the approaches outlined in this paper being used for personal identification, further systematic investigations utilising permitted databases containing cutting-edge digital photos are required. These methods can also be employed in the future in conjunction with those that have already been created in the disciplines of forensic pathology, forensic anthropology, and radiographic recognition and identification procedures.

Acknowledgement

None.

Conflict of Interest

There is no conflict of interest by author.

References

1. Tsubaki, Shun, Junji Morishita, Yosuke Usumoto and Kyoko Sakaguchi, et al. "Sex determination based on a thoracic vertebra and ribs evaluation using clinical chest radiography." Leg Med 27 (2017): 19-24.

   Google Scholar, Crossref

2. Sonoda, Minoru, Masao Takano, Junji Miyahara and Hisatoyo Kato. "Computed radiography utilizing scanning laser stimulated luminescence." Radiology 148 (1983): 833-838.

   Google Scholar, Crossref, Indexed at

3. Matsunobu, Yusuke, Junji Morishita, Yosuke Usumoto, and Miki Okumura, et al. "Bone comparison identification method based on chest computed tomography imaging." Leg Med 29 (2017): 1-5.

   Google Scholar, Crossref, Indexed at

4. Kawazoe, Yusuke, Junji Morishita, Yusuke Matsunobu and Miki Okumura, et al. "A simple method for semi-automatic readjustment for positioning in post-mortem head computed tomography imaging." J Forensic Radiol Imaging 16 (2019): 57-64.

   Google Scholar, Crossref

5. Morishita, Junji, Shigehiko Katsuragawa, Keisuke Kondo and Kunio Doi, et al. "An Automated Patient Recognition Method Based on an Image‐matching Technique Using Previous Chest Radiographs in the Picture Archiving and Communication System Environment." Med Phys 28 (2001): 1093-1097.

   Google Scholar, Crossref, Indexed at

6. Morishita, Junji, Shigehiko Katsuragawa, Yasuo Sasaki, and Kunio Doi, et al. "Potential usefulness of biological fingerprints in chest radiographs for automated patient recognition and identification1." Acad Radiol 11 (2004): 309-315.

   Google Scholar, Crossref