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FORENSIC RADIOLOGY: AN INTELLIGENT METHOD OF AGE AND GENDER ESTIMATION FROM X-RAY SCANNED BONES IMAGES USING CONVOLUTIONAL NEURAL NETWORKS


Article Information

Title: FORENSIC RADIOLOGY: AN INTELLIGENT METHOD OF AGE AND GENDER ESTIMATION FROM X-RAY SCANNED BONES IMAGES USING CONVOLUTIONAL NEURAL NETWORKS

Authors: Adnan Kashif, Hina Shafique, Aqsa Khursheed, Akkasha Latif, Shafqat Ali, Syeda Naila Batool, Muhammad Ahsan, Anum Saher, Fatima Bibi, Hunaina Arshad Chohan, Shumaila Yasin, Syed Naseem Abbas, Ghulam Gilanie

Journal: Spectrum of Engineering Sciences

HEC Recognition History
Category From To
Y 2024-10-01 2025-12-31

Publisher: Sociology Educational Nexus Research Institute

Country: Pakistan

Year: 2025

Volume: 3

Issue: 7

Language: en

Keywords: Forensic RadiologyAN INTELLIGENT METHOD OF AGE AND GENDERESTIMATION FROM X-RAY SCANNED BONES IMAGESUSING CONVOLUTIONAL NEURAL NETWORKS

Categories

Abstract

Determination of identity is always the most demanding aspect of a person, when only bones are left. Identity can be lost due to natural disasters and incidents. Police departments and other law enforcement agencies engage the forensic department to estimate the age and gender when such an event occurs. In this study, a comparative identification method is being utilized on panoramic dental X-rays through the segmentation of morphological features. Which will be extracted, and our model will be trained using DCN by comparing the atlas and cranial measurements for age and gender estimation, respectively. The proposed model is trained and produced a 98% accurate result during the test phase with 840 images of different age and gender groups. This study is being introduced for the very first time in Pakistan. It will help police, forensic, and other law enforcement agencies to make faster, possible their investigation process in economical. It will help to reduce the total amount of DNA.


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