The exponential rise in e-Healthcare technologies has enhanced capabilities for tasks such as computer-aided diagnosis (CAD), health predictions, and telemedicine. However, transmitting patient medical data over wireless or semi-trusted networks presents significant security challenges, including risks of manipulation, misuse, and data breaches. Existing solutions, such as medical image steganography, cryptography, chaotic maps, and permutation-diffusion models, often fall short in addressing computational efficiency, delay, and attack resilience. This paper reviews state-of-the-art models for medical image security, emphasizing quality adaptive steganography and lightweight encryption mechanisms. Key findings suggest that integrating adaptive lightweight encryption with dynamic keying and quality-driven PHR embedding can bolster secure medical data transmission, offering a robust solution for IoMT-driven e-Healthcare services.