Massive high-resolution medical images have become an important medium for medical record storage, disease diagnosis, online consultation and remote diagnosis and treatment to ensure people’s health. Traditional full-image encryption technology is an important means of safeguarding patient privacy. However, for massive high-resolution medical images, traditional encryption technology cannot meet the requirements for high processing speed. Due to the significant separation between organ regions and background regions in medical images, local encryption technology for regions of interest (ROI) in medical images is expected to meet the high processing rate requirements for large volumes of medical images. Meantime, the non-destructiveness of decrypted medical images is necessary to ensure the precision medicine. This paper primarily studies the efficient, secure, and lossless encryption and decryption technology for the local ROI in medical images. The binary edge image of the medical image is obtained using U2-Net, thus the original image is divided into ROI and the region of the background (ROB) according to the positional relationship between the original image and the ROI in the binary image. The ROI bit plane is scrambled using the Chen chaotic system, and the key matrix is generated by the Henon chaotic map to diffuse the scrambled bit plane image. The encrypted ROI and the unencrypted ROB are combined into a ciphertext image. Run-length encoding is used to compress and encode the ROI binary image, then the encoding results are randomly embedded into the ciphertext image, which can achieve lossless decryption while improving security.