Medical Video Transmission Research Articles

Cross-Layer Optimization-Based Asymmetric Medical Video Transmission in IoT Systems

At present, Internet of Things (IoT) networks are attracting much attention since they provide emerging opportunities and applications. In IoT networks, the asymmetric and symmetric studies on medical and biomedical video transmissions have become an interesting topic in both academic and industrial communities. Especially, the transmission process shows the characteristics of asymmetry: the symmetric video-encoding and -decoding processes become asymmetric (affected by modulation and demodulation) once a transmission error occurs. In such an asymmetric condition, the quality of service (QoS) of such video transmissions is impacted by many different factors across the physical (PHY-), medium access control (MAC-), and application (APP-) layers. To address this, we propose a cross-layer optimization-based strategy for asymmetric medical video transmission in IoT systems. The proposed strategy jointly utilizes the video-coding structure in the APP- layer, the power control and channel allocation in the MAC- layer, and the modulation and coding schemes in the PHY- layer. To obtain the optimum configuration efficiently, the proposed strategy is formulated and proofed by a quasi-convex problem. Consequently, the proposed strategy could not only outperform the classical algorithms in terms of resource utilization but also improve the video quality under the resource-limited network efficiently.

Retracted: Quality of experience (QOE) content aware hybrid lean predictive models for medical video transmission over Internet of things (IOT) networks

Lavanya K, Vimala Devi K, Subramaniam M. Quality of experience (QOE) content aware hybrid lean predictive models for medical video transmission over Internet of things (IOT) networks, International Journal of Communication Systems 2021, (https://doi.org/10.1002/dac.4833). The above article published online on 3 June 2021 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor and John Wiley and Sons Ltd. Following publication, it has come to our attention that the people named as the Guest Editors of the Special Issue were being impersonated by a fraudulent entity and the articles were not reviewed in line with the journal's peer review standards. The Editor has determined that the articles do not meet the required scholarly standards of the journal, and therefore has taken the decision to retract the article. We did not find any evidence of misconduct by the authors. The authors have been informed of the decision to retract.

5G Enabled Tactile Internet for Tele-Robotic Surgery

Abstract In today’s communication era, we are speedily moving from various generations of mobile communication technologies to Next Generation mobile communication. Moving from 3G, 4G and 5G, one to the next generation, it includes in-built improvements in various characteristics. The world is collecting traditional information this is huge and providing the same to every corner of the world that creates huge pressure on the core networking and backhaul resources. This paper focuses on combining 5G technologies with mobile edge computing for robotic telesurgery. A huge amount of data is required to continuously transfer over the high-speed network for this process. This process demands high network bandwidth, minimal information loss, minimal delay and real-time response for precise surgery. As of today, useful and cost-effective solutions for medical domain telerobotic surgeries are not preferred yet may be due to the performance limitations of existing communication technologies like 4G. Hence, realtime medical video transmission using 5G enabled tactile (T5ET) internet technology environment is experimented in this research, with a focus on QoS parameters like jitter control, throughput, and delay. Promising results are observed in the evaluation and discussed here which will prominently contribute to the medical domain.

A QoE Evaluation Method for RT-HDMV Based on Multipath Relay Service

Multipath diversity leads to a possible higher performance for real-time high definition video, especially for medical video transmission, which would improve the stability of multiple transmission paths in the symmetrical state, and avoid the potential losses of imaging information in the communication process. Most of the previous works are always based on the single-path end-to-end transmission, although the service had been demonstrated that it is unable to meet the rigorous demand for the RT-HDMV. In the paper, a multipath relay service based on the QoE (quality of experience) evaluation method is proposed for the RT-HDMV (real-time high definition medical video). The method eliminates several of the limitations in the existing methods for some conventional single-path transmission. It can fully utilize the finite network resources and transmission bandwidth to meet the users’ demands of the RT-HDMV to get a better score of the QoE. We use a four-stage framework to evaluate the QoE, which consists of constructing the multipath relay transmission for the RT-HDMV, calculating the weights of diversified QoS parameters in the multipath, designing the load distribution strategy by the mapping between the QoS (quality of service) and QoE, and redefining the rule of the QoE evaluation. Many experiments show that the proposed design scheme achieves weighting of the transmission sub-paths and computes the QoE score. Compared with the state-of-art methods in the single path transmission scene, our framework mainly gains the excellent performance for the RT-HDMV.

Medical Ultrasound Video Coding with H.265/HEVC Based on ROI Extraction.

High-efficiency video compression technology is of primary importance to the storage and transmission of digital medical video in modern medical communication systems. To further improve the compression performance of medical ultrasound video, two innovative technologies based on diagnostic region-of-interest (ROI) extraction using the high efficiency video coding (H.265/HEVC) standard are presented in this paper. First, an effective ROI extraction algorithm based on image textural features is proposed to strengthen the applicability of ROI detection results in the H.265/HEVC quad-tree coding structure. Second, a hierarchical coding method based on transform coefficient adjustment and a quantization parameter (QP) selection process is designed to implement the otherness encoding for ROIs and non-ROIs. Experimental results demonstrate that the proposed optimization strategy significantly improves the coding performance by achieving a BD-BR reduction of 13.52% and a BD-PSNR gain of 1.16 dB on average compared to H.265/HEVC (HM15.0). The proposed medical video coding algorithm is expected to satisfy low bit-rate compression requirements for modern medical communication systems.

Development of a Network Adaptive H.264/AVC Medical Video Transmission System

Network high definition video applications such as video calls and videoconferences have been increasingly developed recent years. When congestions occur and network environment becomes unstable, the network applications have to deal with such issues like delay, packet loss and bandwidth constraints. In this paper, we describe a high definition H.264/AVC video transmission system with network adaptive function based on real-time transport protocol (RTP) and real-time transport control protocol (RTCP). The adaptive system is composed of three components: 1) transmission management (TM) which focuses on network state monitoring, bandwidth allocating and transmission rate control; 2) a feedback-based adaptive forward error correction (AFEC) scheme using Reed Solomon (RS) code; 3) adaptive video encoding (AVE) that adjusts the bitrate of video streaming according to the bandwidth constraint information offered by TM. In our paper, delay, packet loss and bandwidth constraints are generated by the network bottleneck and congestions. Hence, the main idea is to enhance the bitrate of video streaming adapt to the bandwidth constraints. In addition, we integrate AFEC with RTCP to feedback bandwidth status and make the adaptive video streaming more robust under packet loss environment. Here we call it interactive adaptive forward error correction (IAFEC). The test result shows IAFEC can be adaptive to strict bandwidth constraints and high packet loss rates.

Blackfin Processor Based Secure Medical Image, Audio and Video Transmission Technique for Telemedicine Considering Online Application

Telemedicine means transmission of medical data between users for diagnosis is one of the emerging fields in medicine. During transmission of medical data such as images, videos etc over internet huge bandwidth are needed. Resolution factor and number of images per diagnosis makes even the size of the medical image and video that belongs to a single patient to be very large in size. So there is an immense need for efficient compression techniques for use in compressing these medical data to decrease the storage space and efficiency of transfer the images over network for access to electronic patient records. And also during transmission security of the data is very important. This project summarizes the different transformation methods used in compression as compression is one of the techniques that reduces the amount of data needed for storage or transmission of information, and the security technique used for secure transmission of data. Here we outlines the comparison of transformation methods such as DPCM (Differential Pulse Code Modulation), and prediction improvement in DPCM transformation step of compression which is efficient in both entropy reduction and computational complexity. The improved DPCM transformation increases the energy compaction of prediction model and as a result reduces entropy value of transformed image. After transforming the image Huffman encoding used to compress the image. Security is then added to the compressed image formed by signature analysis. Finally each process involved in detecting hard exudates take up a icon in a single window called Graphical User Interface (GUI) window which will be an exclusive window for detecting hard exudates. The processed resultant image can be examined comfortably at its earlier stages and thus reducing the examining time. The result is analyzed using MATLAB and implemented in hardware.

A Tutorial for Emerging Wireless Medical Video Transmission Systems [Wireless Corner

The wireless transmission of medical video is expected to see significant growth in the coming years. This is primarily due to the expected availability of significant bandwidth in the next-generation of wireless communications networks, and the emergence of effective wireless video-compression standards. The design of wireless medical video transmission systems presents unique requirements for error-resilience and clinical validation. We present a tutorial introduction to the most important components of a wireless medical video transmission system. We focus on video-encoding requirements for error resilience, quality-of-service transmission, and diagnostic validation. Whenever possible, we give references to open-source software and provide references to the literature. We demonstrate the basic principles through the use of simple examples of stroke ultrasound videos.

Flexible Macroblock Ordering for Context-Aware Ultrasound Video Transmission over Mobile WiMAX

The most recent network technologies are enabling a variety of new applications, thanks to the provision of increased bandwidth and better management of Quality of Service. Nevertheless, telemedical services involving multimedia data are still lagging behind, due to the concern of the end users, that is, clinicians and also patients, about the low quality provided. Indeed, emerging network technologies should be appropriately exploited by designing the transmission strategy focusing on quality provision for end users. Stemming from this principle, we propose here a context-aware transmission strategy for medical video transmission over WiMAX systems. Context, in terms of regions of interest (ROI) in a specific session, is taken into account for the identification of multiple regions of interest, and compression/transmission strategies are tailored to such context information. We present a methodology based on H.264 medical video compression and Flexible Macroblock Ordering (FMO) for ROI identification. Two different unequal error protection methodologies, providing higher protection to the most diagnostically relevant data, are presented.

Adaptive Transmission of Medical Image and Video Using Scalable Coding and Context-Aware Wireless Medical Networks

The aim of this paper is to present a novel platform for advanced transmission of medical image and video, introducing context awareness in telemedicine systems. Proper scalable image and video compression schemes are applied to the content according to environmental properties (i.e., the underlying network status, content type, and the patient status). The transmission of medical images and video for telemedicine purposes is optimized since better content delivery is achieved even in the case of low-bandwidth networks. An evaluation platform has been developed based on scalable wavelet compression with region-of-interest support for images and adaptive H.264 coding for video. Corresponding results of content transmission over wireless networks (i.e., IEEE 802.11e, WiMAX, and UMTS) have proved the effectiveness and efficiency of the platform.