ABSTRACT
This study proposes a unifying framework for m-Health video communication systems that provides for the joint optimization of video quality, bitrate demands, and encoding time. The framework is video modality and infrastructure independent and facilitates adaptation to the best available encoding mode that satisfies underlying technology and application imposed constraints. The scalability of the proposed algorithm is demonstrated using different HEVC encoding configurations and realistic modelling of 802.11× wireless infrastructure for emergency scenery and response videos. Extensive experimentation shows that a jointly optimal solution in the encoding time, bitrate, and video quality space is feasible.
Subject(s)
Disasters , Emergency Medicine/methods , Video Recording/methods , Wireless Technology , Algorithms , Computer Communication Networks , Decision Support Techniques , Humans , Telemedicine/instrumentation , Wireless Technology/instrumentationABSTRACT
The emergence of the new, High Efficiency Video Coding (HEVC) standard, combined with wide deployment of 4G wireless networks, will provide significant support toward the adoption of mobile-health (m-health) medical video communication systems in standard clinical practice. For the first time since the emergence of m-health systems and services, medical video communication systems can be deployed that can rival the standards of in-hospital examinations. In this paper, we provide a thorough overview of today's advancements in the field, discuss existing approaches, and highlight the future trends and objectives.
Subject(s)
Computer Communication Networks , Telemedicine/instrumentation , Algorithms , Communication , Diagnosis, Computer-Assisted , Equipment Design , Humans , Signal Processing, Computer-Assisted , Telemedicine/methods , Video Recording , Wireless TechnologyABSTRACT
Emerging high efficiency video compression methods and wider availability of wireless network infrastructure will significantly advance existing m-health applications. For medical video communications, the emerging video compression and network standards support low-delay and high-resolution video transmission, at the clinically acquired resolution and frame rates. Such advances are expected to further promote the adoption of m-health systems for remote diagnosis and emergency incidents in daily clinical practice. This paper compares the performance of the emerging high efficiency video coding (HEVC) standard to the current state-of-the-art H.264/AVC standard. The experimental evaluation, based on five atherosclerotic plaque ultrasound videos encoded at QCIF, CIF, and 4CIF resolutions demonstrates that 50% reductions in bitrate requirements is possible for equivalent clinical quality.
Subject(s)
Algorithms , Data Compression/methods , Image Interpretation, Computer-Assisted/methods , Signal Processing, Computer-Assisted , Telemedicine/methods , Ultrasonography/methods , Video Recording/methodsABSTRACT
This correspondence presents a fast recursive shortest spanning tree algorithm for image segmentation and edge detection. The conventional algorithm requires a complexity of o(n(2)) for an image of n pixels, while the complexity of our approach is bounded by O(n), which is a new lower bound for algorithms of this kind. The total memory requirement of our fast algorithm is 20% smaller.
