<![CDATA[Medical image security is a crucial aspect of maintaining the integrity and authenticity of diagnostic data, particularly during digital transmission and storage processes that are vulnerable to manipulation. Minor modifications to pixels can lead to misdiagnosis; thus, protection methods are required to verify integrity without compromising visual quality. However, previous studies still face a trade-off between system complexity, computational efficiency, and tamper detection capabilities. This research aims to develop a medical image watermarking method capable of efficiently detecting changes in diagnostic areas with minimal distortion. The proposed method integrates automated Region of Interest (ROI) segmentation based on Otsu thresholding, 1-LSB watermark embedding in the Region of Non-Interest (RONI), and authentication based on SHA-256 and ECDSA digital signatures. The primary contribution of this study is an integrated framework that combines automated segmentation and cryptographic authentication to maintain image integrity without sacrificing clinical information. Experimental results demonstrate that the method maintains high image quality, with an average PSNR of 75.04 dB, low MSE, and the highest SSIM of 0.9999975. This performance is achieved through a small payload (99 bytes) that modifies only 1.21% of pixels in the RONI. In terms of efficiency, the method exhibits relatively fast computational performance with average embedding and extraction times of 0.14 seconds and 0.095 seconds, respectively, on 256×256 pixel images using an AMD Ryzen 5 5600H and 16 GB RAM. The system is capable of detecting ROI manipulation, identifying global payload damage, and remains valid under RONI changes, although it remains limited against large-scale manipulation due to the fragile nature of the LSB technique.]]>
