Optimized Security Measures: Whale-inspired Manta Ray Foraging Optimization Based Watermarking for Medical Image Data

Localization Robust data protection protocols are necessary as the use of 3D imaging techniques in treatment and diagnosis grows. Watermarking is a crucial method in this context. The security and effectiveness of the watermarking techniques currently in use, however, have certain problems. The objective for this research is to find a new approach that can increase the durability of watermarking for 3D medical data as well as fortify defenses against unauthorized access and manipulation. In this paper, we present a novel whale-inspired manta ray foraging optimization (W-MRFO) method for achieving the ideal balance between invisibility and insertion capacity. By refining the watermark insertion process, the system aims to strike a balance between personal and analytic image reliability, taking cues from the agile foraging activities of manta rays and the collaborative actions of whale groups. We evaluate the proposed W-MRFO approach on a comprehensive set of 3D imaging samples. The application of linear discriminant analysis (LDA) to minimize the dimension could reduce inaccuracy. The recommended W-MRFO approach is implemented and the effectiveness of the watermarking is examined, using a Python program. The outcomes demonstrate how well the recommended technique for watermarking clinical images performs, providing robust protection against alteration and unauthorized access.

I. Introduction

Images of the human body's inside structures and biological functions recorded by imaging modalities like CT scans, X-rays, MRIs, ultrasounds and radiation therapy are known as medical image data. Medical diagnosis, therapy planning and illness monitoring rely heavily on these images. Anatomical and pathological details can be better understood with the use of several imaging modalities [1].