The New Wave of Biometric Identification with AI Approaches in X-ray and MRI Data

In the area of biometric identification, the integration of AI techniques with X-ray and MRI data is heralding a new era of possibilities. This paper explores innovative AI approaches specifically designed for this purpose, highlighting their potential to deliver unparalleled levels of accuracy and security in biometric identification. The research presented herein not only offers a transformative shift in the way biometric data is analysed but also holds profound implications for both medical diagnostics and high-security sectors. Biometric identification is a crucial aspect of security and healthcare. This research explores the integration of AI techniques with X-ray and MRI data to revolutionise biometric identification. We introduce innovative approaches that leverage medical imaging data to achieve unprecedented levels of accuracy and security. The potential impact of this research is far-reaching. In the medical field, it can lead to more accurate patient identification and personalised treatments. In high-security sectors, it can enhance access control and identity verification. The fusion of AI and medical imaging data presents new opportunities for enhancing both healthcare and security systems. This paper highlights the transformative potential of integrating AI with X-ray and MRI data for biometric identification. The innovative approaches presented offer a glimpse into a future where biometric data analysis is more accurate, secure, and applicable in diverse domains, benefiting individuals and organisations alike.

Authors

Publication Details

Journal
AVE Trends in Intelligent Computer Letters
Published
2025-03-01
DOI
https://doi.org/10.64091/aticl.2025.000091
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.00
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article

The New Wave of Biometric Identification with AI Approaches in X-ray and MRI Data

S. Silvia Priscila, Gnaneswari Gnanaguru, D. Femi, Kawsher Rahman et al.
AVE Trends in Intelligent Computer Letters
Brain Tumor Detection and Classification
article

The New Wave of Biometric Identification with AI Approaches in X-ray and MRI Data

S. Silvia Priscila, Gnaneswari Gnanaguru, D. Femi, Kawsher Rahman, M. Sakthivanitha
article en

Abstract

In the area of biometric identification, the integration of AI techniques with X-ray and MRI data is heralding a new era of possibilities. This paper explores innovative AI approaches specifically designed for this purpose, highlighting their potential to deliver unparalleled levels of accuracy and security in biometric identification. The research presented herein not only offers a transformative shift in the way biometric data is analysed but also holds profound implications for both medical diagnostics and high-security sectors. Biometric identification is a crucial aspect of security and healthcare. This research explores the integration of AI techniques with X-ray and MRI data to revolutionise biometric identification. We introduce innovative approaches that leverage medical imaging data to achieve unprecedented levels of accuracy and security. The potential impact of this research is far-reaching. In the medical field, it can lead to more accurate patient identification and personalised treatments. In high-security sectors, it can enhance access control and identity verification. The fusion of AI and medical imaging data presents new opportunities for enhancing both healthcare and security systems. This paper highlights the transformative potential of integrating AI with X-ray and MRI data for biometric identification. The innovative approaches presented offer a glimpse into a future where biometric data analysis is more accurate, secure, and applicable in diverse domains, benefiting individuals and organisations alike.

AVE Trends in Intelligent Computer LettersVol. 1(1)
Openalex Percentile: Top 72%
Brain Tumor Detection and Classification
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The New Wave of Biometric Identification with AI Approaches in X-ray and MRI Data — S. Silvia Priscila, Gnaneswari Gnanaguru, et al. · AVE Trends in Intelligent Computer Letters (2025) | TGRS Research Map | TGRS