Tele-training in surgical education has not been effectively implemented. There is a stringent need for a high transmission rate, reliability, throughput, and reduced distortion for high-quality video transmission in the real-time network. This work aims to propose a system that improves video quality during real-time surgical tele-training. The proposed approach aims to minimise the video frame’s total distortion, ensuring better flow rate allocation and enhancing the video frames’ reliability. The proposed system consists of a proposed algorithm for Enhancing Video Quality, Distorting Minimization, Bandwidth efficiency, and Reliability Maximization called (EVQDMBRM) algorithm. The proposed algorithm reduces the video frame’s total distortion. In addition, it enhances the video quality in a real-time network by dynamically allocating the flow rate at the video source and maximizing the transmission reliability of the video frames. The result shows that the proposed EVQDMBRM algorithm improves the video quality with the minimized total distortion. Therefore, it improves the Peak Signal to Noise Ratio (PSNR) average by 51.13 dB against 47.28 dB in the existing systems. Furthermore, it reduces the video frames processing time average by 58.2 milliseconds (ms) against 76.1, and the end-to-end delay average by 114.57 ms against 133.58 ms comparing to the traditional methods. The proposed system concentrates on minimizing video distortion and improving the surgical video transmission quality by using an EVQDMBRM algorithm. It provides the mechanism to allocate the video rate at the source dynamically. Besides that, it minimizes the packet loss ratio and probing status, which estimates the available bandwidth.
相似文献Mixed Reality (MR) surgery has not been effectively implemented in telemedicine due to strict requirements of security and delay minimization during real-time video transmission. Hence, this paper aims to propose a novel solution for Surgical Telepresence with highly secured and faster real-time video transmission. The proposed system consists of three components: Authentication (Pre-surgery), Data transmission (During-Surgery), and Storage (Post-Surgery). For Authentication, Pass-Matrix technique is used at both ends to provide graphical passwords. During the surgery, a hybrid system is used to provide highly secured and faster real-time video transmission. This system includes a Feistel Encryption System (FES), Modified Scaled Zhongtang Chaotic System (M-SCZS), and Modified Advanced Encryption System (M-AES) algorithm. After Surgery, the transmitted data are stored using the Information Accountability Framework (IAF) for future purposes. The results are obtained from the during-surgery stage for jaw, breast, and bowel surgery. Both solutions are simulated in MATLAB on a personal computer with average processing capability. The proposed solution improves the entropy from 7.733~7.782 to 7.798–7.996 and reduces the processing time from 8.642~9.911 s/frames to 5.071~6.563 s/frames. The proposed focus on reducing the total processing time for the encryption and decryption process with improving security during the surgery process. Finally, this solution provides a fast security system for surgical telepresence that helps both local and remote surgeons for secure real-time communication. The complexity for this work need to know the used chaotic method, the values of the chaotic parameters and for which this method was used, in addition to the complexity of state of the art.
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