Zinonas C. Antoniou

High-Resolution, Low-Delay, and Error-Resilient Medical Ultrasound Video Communication Using H.264/AVC Over Mobile WiMAX Networks

In this study, we describe an effective video communication framework for the wireless transmission of H.264/AVC medical ultrasound video over mobile WiMAX networks. Medical ultrasound video is encoded using diagnostically driven, error resilient encoding, where quantization levels are varied as a function of the diagnostic significance of each image region. We demonstrate how our proposed system allows for the transmission of high-resolution clinical video that is encoded at the clinical acquisition resolution and can then be decoded with low delay. To validate performance, we perform OPNET simulations of mobile WiMAX medium access control and physical layers characteristics that include service prioritization classes, different modulation and coding schemes, fading channels conditions, and mobility. We encode the medical ultrasound videos at the 4CIF (704×576) resolution that can accommodate clinical acquisition that is typically performed at lower resolutions. Video quality assessment is based on both clinical (subjective) and objective evaluations.

High efficiency video coding for ultrasound video communication in m-health systems

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.

Abdominal Aortic Aneurysm medical video transmission

Abdominal Aortic Aneurysm (AAA) is responsible for approximately 1.3% of all deaths among men over the age of 65. Given the fact that once an aortic rupture occurs mortality rates are estimated between 80%-90%, national AAA population screening programs are currently established as an effective prevention policy. Driven by the latest advances in mobile-health (m-health) systems and services, and more specifically medical video transmission telemedicine systems, the current study is directed towards establishing a AAA m-health medical video transmission framework for mass population screening, remote diagnosis, and emergency incidents. A new clinical evaluation rating scheme evaluates the diagnostic capacity of different encoding setups for transmission over 3.5G wireless networks. Flexible Macroblock Ordering and Redundant Slices, H.264/AVC features, are used for diagnostically relevant and resilient encoding. Preliminary results show that the proposed setting is capable of communicating diagnostically robust AAA ultrasound video.

A workflow system for virtual screening in cancer chemoprevention

Computer-aided drug discovery techniques have been widely used in recent years to support the development of new pharmaceuticals. Virtual screening, the computational counterpart of experimental screening, attempts to replicate the results from in vitro and in vivo methods through the use of in silico models and tools. This paper presents the LISIs platform; a web based scientific workflow system for virtual screening that has been implemented primarily for the discovery of chemoprevention agents. We describe the overall design of the system as well as the implementation of its various components. Indicative results from early applications of the system are also presented to illustrate its potential uses and functionalities.

The use of H.264/AVC and the emerging high efficiency video coding (HEVC) standard for developing wireless ultrasound video telemedicine systems

For wireless medical video communications, the emerging high-efficiency video coding (HEVC) standard and network standards support low-delay and high-resolution video transmission, at the clinically acquired resolution and frame rates. Ultimately, the goal is to support remote diagnosis for emergency incidents in standard clinical practice. Clinical video quality assessment needs to be clearly defined in terms of clinical criteria. This paper investigates the advantages of the HEVC standard over the H.264/AVC standard and the wireless transmission of high-resolution stroke ultrasound videos over mobile WiMAX networks. We test different HEVC modes that include high-efficiency and low-complexity configurations combined with low-delay and random access. The results are compared against similar H.264/AVC configurations. The experimental evaluation demonstrates significant reductions in bitrate requirements for equivalent clinical quality of approximately 37%. Moreover, careful selection of network parameters based on objective and subjective clinical criteria demonstrates that mobile WiMAX can be used to communicate low-delay H.264/AVC ultrasound video at the clinically acquired resolution.

Adaptive emergency scenery video communications using HEVC for responsive decision support in disaster incidents

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.

An Overview of mHealth Medical Video Communication Systems

Significant technological advances over the past decade have led mHealth systems and services to a remarkable growth. It is anticipated that such systems and services will soon be established in standard clinical practice. MHealth medical video communication systems progression has been primarily driven by associated advances in video coding and wireless networks technologies. Responsive, reliable, and of high-diagnostic quality systems are now feasible. Such systems build on compression ratios and error resilience tools found in current state-of-the-art video coding standards, linked with low-delay and high-bandwidth communications facilitated by new wireless systems. To achieve this however, these systems need to be diagnostically driven. In other words, both encoding and transmission need to adapt to the underlying medical video modality’s properties, for maximizing the communicated video’s clinical capacity. Moreover, the proper mechanisms should be developed that will guarantee the quality of the transmitted clinical content. Current video quality assessment (VQA) algorithms are unsuccessful to replicating clinical evaluation performed by the relevant medical experts. Clearly, there is a demand for new clinical VQA (c-VQA) metrics.

Dynamic Network Adaptation for Real-Time Medical Video Communication

The wider adoption of mHealth video communication systems in standard clinical practice requires adequate levels of clinical video quality to support reliable diagnosis. The latter dictates that real-time adaptation to time-varying wireless networks’ state to guarantee clinically acceptable performance throughout the streaming session, while conforming to device capabilities for supporting real-time encoding. In this study we propose a multi-objective optimization framework that jointly maximizes the encoded video’s quality while minimizing bitrate demands and encoding time. Experimental investigation shows that the proposed framework can provide for efficient real-time adaptation at a Group of Pictures (GOP) level, demonstrating significant gains over static approaches.

Electronic Health Record Application Support Service Enablers.

There is a huge need for open source software solutions in the healthcare domain, given the flexibility, interoperability and resource savings characteristics they offer. In this context, this paper presents the development of three open source libraries - Specific Enablers (SEs) for eHealth applications that were developed under the European project titled “Future Internet Social and Technological Alignment Research” (FI-STAR) funded under the “Future Internet Public Private Partnership” (FI-PPP) program. The three SEs developed under the Electronic Health Record Application Support Service Enablers (EHR-EN) correspond to: a) an Electronic Health Record enabler (EHR SE), b) a patient summary enabler based on the EU project “European patient Summary Open Source services” (epSOS SE) supporting patient mobility and the offering of interoperable services, and c) a Picture Archiving and Communications System (PACS) enabler (PACS SE) based on the dcm4che open source system for the support of medical imaging functionality. The EHR SE follows the HL7 Clinical Document Architecture (CDA) V2.0 and supports the Integrating the Healthcare Enterprise (IHE) profiles (recently awarded in Connectathon 2015). These three FI-STAR platform enablers are designed to facilitate the deployment of innovative applications and value added services in the health care sector. They can be downloaded from the FI-STAR cataloque website. Work in progress focuses in the validation and evaluation scenarios for the proving and demonstration of the usability, applicability and adaptability of the proposed enablers.

LiSIs: An Online Scientific Workflow System for Virtual Screening

Modern methods of drug discovery and development in recent years make a wide use of computational algorithms. These methods utilise Virtual Screening (VS), which is the computational counterpart of experimental screening. In this manner the in silico models and tools initial replace the wet lab methods saving time and resources. This paper presents the overall design and implementation of a web based scientific workflow system for virtual screening called, the Life Sciences Informatics (LiSIs) platform. The LiSIs platform consists of the following layers: the input layer covering the data file input; the pre-processing layer covering the descriptors calculation, and the docking preparation components; the processing layer covering the attribute filtering, compound similarity, substructure matching, docking prediction, predictive modelling and molecular clustering; post-processing layer covering the output reformatting and binary file merging components; output layer covering the storage component. The potential of LiSIs platform has been demonstrated through two case studies designed to illustrate the preparation of tools for the identification of promising chemical structures. The first case study involved the development of a Quantitative Structure Activity Relationship (QSAR) model on a literature dataset while the second case study implemented a docking-based virtual screening experiment. Our results show that VS workflows utilizing docking, predictive models and other in silico tools as implemented in the LiSIs platform can identify compounds in line with expert expectations. We anticipate that the deployment of LiSIs, as currently implemented and available for use, can enable drug discovery researchers to more easily use state of the art computational techniques in their search for promising chemical compounds. The LiSIs platform is freely accessible (i) under the GRANATUM platform at: http://www.granatum.org and (ii) directly at: http://lisis.cs.ucy.ac.cy.