With the increasing importance of using medical images to diagnose diseases, it is crucial to protect these images during network transfers and unauthorized use of medical imaging data can have serious consequences, including threats of privacy and incorrect diagnoses that may endanger patient’s lives. As a result, we propose a novel image encryption algorithm for various medical images. Our approach is mostly based on the confusion and diffusion process. The confusion process begins with image-splitting and rearranging the image pixel positions using customized patterns, followed by 180-degree block rotations, and block-level permutations. The primary idea behind our methodology is to generate a secret key utilizing a chaotic logistic map that carefully considers the characteristics of the original image. Using this key, the diffusion process changes the pixel values, making the image unreadable without proper authorization. The proposed methodology exceeds existing approaches in terms of key sensitivity and adaptability against statistical threats, according to systematic security assessments. Additionally, it reduces the pixel correlation, which protects it against differential attacks. In order to maintain patient privacy and trust in the applications of telemedicine, our contribution is crucial to the safe transmission and protection of medical images.