Manzoor Razaak

A Study on Quality Assessment for Medical Ultrasound Video Compressed via HEVC

The quality of experience and quality of service provided in the healthcare sector are critical in evaluating the reliable delivery of the healthcare services provided. Medical images and videos play a major role in modern e-health services and have become an integral part of medical data communication systems. The quality evaluation of medical images and videos is an essential process, and one of the ways of addressing it is via the use of quality metrics. In this paper, we evaluate the performance of seven state-of-the-art video quality metrics with respect to compressed medical ultrasound video sequences. We study the performance of each video quality metric in representing the diagnostic quality of the video, by evaluating the correlation of each metric with the subjective opinions of medical experts. The results indicate that the visual information fidelity, structural similarity index, and universal quality index metrics show good correlation with the subjective scores provided by medical experts. The tests also investigate the performance of the emerging video compression standard, high-efficiency video coding-HEVC, for medical ultrasound video compression. The results show that, using HEVC with the considered ultrasound video sequences, a diagnostically reliable compressed ultrasound video can be obtained for compression with values of the quantization parameter up to 35.

Medical image and video quality assessment in e-health applications and services

Healthcare services are increasingly using medical images and video in their applications. Quality assessment can be performed via image quality evaluation metrics. However, due to the specific nature of the associated data, quality evaluation of medical images poses several issues. In this paper, we provide an insight into medical image quality evaluation, by discussing the issues faced and the current trends in the literature. Based on the analysis of the medical and technical literature, three broad categories of quality evaluation metrics are presented. The different methodologies are compared in different environments and services and recommendations for future research are provided.

Rate-distortion and Rate-quality Performance Analysis of HEVC Compression of Medical Ultrasound Videos☆

Abstract The emerging video compression standard High Efficiency Video Coding (HEVC) promises to provide bitrate savings of up to 50% compared to its predecessor H.264 standard. Due to its remarkable compression performance, HEVC is expected to be extensively used for telemedicine applications. Therefore, it is important to analyse the compression performance of HEVC and its impact on the diagnostic and perceptual quality of medical videos. In this paper, medical ultrasound video sequences compressed via HEVC were subjectively assessed by medical experts and non-experts and the subjective scores obtained were then used to analyze the compression performance of HEVC in terms of acceptable diagnostic and perceptual video quality. The rate-distortion and rate-quality performance of HEVC with respect to medical ultrasound videos is presented. The bitrate and the Quantization Parameter (QP) range at which HEVC can provide acceptable diagnostic and perceptual quality for medical ultrasound videos are discussed.

Medical video streaming utilizing MPEG-DASH

This paper presents an analysis of medical video streaming based on the Dynamic Adaptive Streaming over HTTP (DASH) standard from the Moving Picture Experts Group (MPEG).We propose two adaptation approaches at the client and evaluate parameters of the Quality of Experience (QoE), i.e., the quality perceived by the users, by investigating the number and duration of re-buffering events, the added time in the playout, and the Peak Signal-to-Noise Ratio (PSNR) of the medical video frames. The results show that the selection of MPEG-DASH related parameters and the adaptation approach at the client result in improved quality of the medical video streaming. In the end, we discuss how the elaborated approaches and results could be utilized to facilitate and enhance telemedicine applications.

A methodology to evaluate the effect of video compression on the performance of analytics systems

The Image Library for Intelligent Detection Systems (i-LIDS) provides benchmark surveillance datasets for analytics systems. This paper proposes a methodology to investigate the effect of compression and frame-rate reduction, and to recommend an appropriate suite of degraded datasets for public release. The library consists of six scenarios, including Sterile Zone (SZ) and Parked Vehicle (PV), which are investigated using two different compression algorithms (H.264 and JPEG) and a number of detection systems. PV has higher spatio-temporal complexity than the SZ. Compression performance is dependent on scene content hence PV will require larger bit-streams in comparison with SZ, for any given distortion rate. The study includes both industry standard algorithms (for transmission) and CCTV recorders (for storage). CCTV recorders generally use proprietary formats, which may significantly affect the visual information. Encoding standards such as H.264 and JPEG use the Discrete Cosine Transform (DCT) technique, which introduces blocking artefacts. The H.264 compression algorithm follows a hybrid predictive coding approach to achieve high compression gains, exploiting both spatial and temporal redundancy. The highly predictive approach of H.264 may introduce more artefacts resulting in a greater effect on the performance of analytics systems than JPEG. The paper describes the two main components of the proposed methodology to measure the effect of degradation on analytics performance. Firstly, the standard tests, using the ‘f-measure’ to evaluate the performance on a range of degraded video sets. Secondly, the characterisation of the datasets, using quantification of scene features, defined using image processing techniques. This characterization permits an analysis of the points of failure introduced by the video degradation.

CUQI: cardiac ultrasound video quality index.

Abstract. Medical images and videos are now increasingly part of modern telecommunication applications, including telemedicinal applications, favored by advancements in video compression and communication technologies. Medical video quality evaluation is essential for modern applications since compression and transmission processes often compromise the video quality. Several state-of-the-art video quality metrics used for quality evaluation assess the perceptual quality of the video. For a medical video, assessing quality in terms of “diagnostic” value rather than “perceptual” quality is more important. We present a diagnostic-quality–oriented video quality metric for quality evaluation of cardiac ultrasound videos. Cardiac ultrasound videos are characterized by rapid repetitive cardiac motions and distinct structural information characteristics that are explored by the proposed metric. Cardiac ultrasound video quality index, the proposed metric, is a full reference metric and uses the motion and edge information of the cardiac ultrasound video to evaluate the video quality. The metric was evaluated for its performance in approximating the quality of cardiac ultrasound videos by testing its correlation with the subjective scores of medical experts. The results of our tests showed that the metric has high correlation with medical expert opinions and in several cases outperforms the state-of-the-art video quality metrics considered in our tests.

Content-aware packet scheduling strategy for medical ultrasound videos over LTE wireless networks

Abstract In parallel to the advancements in communication technologies, telemedicine research has continually adapted to develop various healthcare applications. The latest wireless technology Long-Term Evolution(LTE) is being increasingly deployed across developed countries and rapidly adopted by developing countries. In this paper, a content-aware packet scheduling approach for medical ultrasound videos is proposed. The contribution of this work is introducing a utility function based on the temporal complexity of the video frames. The utility function is used with four schedulers to prioritise the video packets based on their temporal complexity and type of frame (e.g. I frame). The results show that the utility function improves the packet delay performance obtained in our simulation when compared with content-unaware approach. Further, gain in average PSNR and SSIM are also observed in the received video quality. Research on content-aware packet scheduling for telemedicine applications over advanced wireless networks is limited and our work contributes towards addressing this research gap.

Applicability of Existing Objective Metrics of Perceptual Quality for Adaptive Video Streaming.

Objective video quality metrics are designed to estimate thequality of experience of the end user. However, these objectivemetrics are usually validated with video streams degraded undercommon dist ...

DASH-based video transmission over LTE networks

This paper proposes an approach for the evaluation of DASH-based video transmission from a server located in a Content Delivery Network (CDN) to multiple LTE users. The approach is based on utilizing an analytical model for the HTTP/TCP transmission in the wired/core link, and simulation traces for the packet transmission in the wireless/access link. The core and access link are separately considered by using the Wireless Transmission Control Protocol (WTCP) at the eNodeB, and three scheduling approaches are used for delivering the video packets in the access link. Therefore, in our proposed approach, we emulate DASH-based end-to-end video delivery and observe how the scheduling strategy affects the video streaming quality depending on the number of users in the system.