Cross-Layer Design for Optimized Region of Interest of Ultrasound Video Data Over Mobile WiMAX

Abstract

The application of advanced error concealment techniques applied as a post-process to conceal lost video information in error-prone channels, such as the wireless channel, demand additional processing at the receiver. This increases the delivery delay and needs more computational power. However, in general, only a small region within medical video is of interest to the physician and thus if only this area is considered, the number of computations can be curtailed. In this paper we present a technique whereby the Region of Interest (ROI) specified by the physician is used to delimit the area where the more complex concealment techniques are applied. A cross layer design approach in mobile WiMAX wireless communication environment is adopted in this paper to provide an optimized Quality of Experience (QoE) in the region that matters most to the mobile physician while relaxing the requirements in the background, ensuring real-time delivery. Results show that a diagnostically acceptable Peak Signal-to-Noise-Ratio (PSNR) of about 36 dB can still be achieved within reasonable decoding time.

Mobile-health: A review of current state in 2015

“…This solution enables clinicians through an ICT platform to insert new knowledge for multisource data management in remote health monitoring. In [31], a cross layer design for a Wi-Max in order to deliver ultrasound video data through mobile devices is presented. Finally, a virtual reality-based surgical simulator for the mandibular angle reduction on a CUD-based platform is presented in [32].…”

Mechanisms for QoE optimisation of Video Traffic: A review paper

“…Work in (Debono et al, 2012) address the issue of high delay computational power caused by video error concealment techniques at receivers. The QoE of the region of a mobile physician's interest is optimised by adopting a cross-layer design approach in mobile worldwide interoperability for microwave access wireless communication environment while ensuring real-time delivery.…”

Exploiting Geo-Distributed Clouds for a E-Health Monitoring System With Minimum Service Delay and Privacy Preservation

“…In a resource allocation scheme, we need to design a matrix U to satisfy condition (10). We present how eigenvalue could facilitate the scheme design.…”

“…When applying geo-distributed clouds for e-health monitoring systems, how to minimize the service delay is a challenging research problem due to the user mobility and the distributed management of cloud servers. Some research works [7]- [10] suggest to utilize the location information of cloud servers in resource allocation to reduce the service delay, while not consider e-health monitoring systems with special service delay requirements. A special-tailored distributed resource allocation scheme for an ehealth monitoring system is of great research value and practical significance.…”