Digital Forensic Approach for Medical Image Manipulation Detection Based on Variance Map and Error Level Analysis
DOI:
https://doi.org/10.71417/jitie.v1i2.39Keywords:
Digital Forensics, Manipulation Detection, Medical Images, Variance MapAbstract
Forgery of medical radiological images, such as CT scans, can lead to serious clinical and legal implications, necessitating robust digital forensic techniques capable of identifying subtle changes in medical images. This research develops an image manipulation detection system based on Variance Map analysis and Error Level Analysis (ELA) as the primary methods. These are reinforced by several supporting techniques, including Fast Fourier Transform (FFT), Local Binary Pattern (LBP), Canny edge detection, and copy-move examination for detecting local repetition patterns. The system is designed to independently analyze a single medical image and produce visual indicators that reveal anomalies in noise patterns, compression artifacts, or textural structure. Testing results indicate that this multi-method approach successfully highlights areas suspected of undergoing digital modification, providing a forensic overview that can serve as initial input for medical image validation. Overall, this study demonstrates that integrating multiple digital forensic methods can significantly enhance the accuracy of manipulation identification in radiological images.
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Copyright (c) 2025 Mashal Tama Ulwan, Rafa Muhammad Indra, Abimanyu Yudha Wiratama (Author)
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