The impact of specialty settings on the perceived quality of medical ultrasound video

Health care professionals are increasingly viewing medical images and videos in a variety of environments. The perception of medical visual information across all specialties, career stages, and practice settings are critical to patient care and patient safety. Visual signal distortions, such as various types of noise and artifacts arising in medical imaging, affect the perceptual quality of visual content and potentially impact diagnoses. To optimize clinical practice, it is of fundamental importance to understand the way medical experts perceive visual quality. Psychophysical studies have been undertaken to evaluate the impact of visual distortions on the perceived quality of medical images and videos. However, very little research has been conducted on how speciality settings affect the perception of visual quality. In this paper, we investigate whether and how radiologists and sonographers differently perceive the quality of compressed ultrasound videos, via a dedicated subjective experiment. The findings can be used to develop useful solutions for improved visual experience and better image-based diagnoses

The impact of specialty settings on the perceived quality of medical ultrasound video

Health care professionals are increasingly viewing medical images and videos in a variety of environments. The perception of medical visual information across all specialties, career stages, and practice settings are critical to patient care and patient safety. Visual signal distortions, such as various types of noise and artifacts arising in medical imaging, affect the perceptual quality of visual content and potentially impact diagnoses. To optimize clinical practice, it is of fundamental importance to understand the way medical experts perceive visual quality. Psychophysical studies have been undertaken to evaluate the impact of visual distortions on the perceived quality of medical images and videos. However, very little research has been conducted on how speciality settings affect the perception of visual quality. In this paper, we investigate whether and how radiologists and sonographers differently perceive the quality of compressed ultrasound videos, via a dedicated subjective experiment. The findings can be used to develop useful solutions for improved visual experience and better image-based diagnoses

Wireless Communication Options for a Mobile Ultrasound System

A mobile ultrasound system has been developed, which makes ultrasound examinations possible in harsh environments without reliable power sources, such as ambulances, helicopters, war zones, and disaster sites. The goal of this project was to analyze three different wireless communication technologies that could be integrated into the ultrasound system for possible utilization in remote data applications where medical information may be transmitted from the mobile unit to some centralized base station, such as an emergency room or field hospital. By incorporating wireless telecommunication technology into the design, on site medical personnel can be assisted in diagnostic decisions by remote medical experts. The wireless options that have been tested include the IEEE 802.11g standard, mobile broadband cards on a 3G cellular network, and a mobile satellite terminal. Each technology was tested in two phases. In the first phase, a client/server application was developed to measure and record general information about the quality of each link. Four different types of tests were developed to measure channel properties such as data rate, latency, inter-arrival jitter, and packet loss using various signal strengths, packet sizes, network protocols, and traffic loads. In the second phase of testing, the H.264 Scalable Video Codec (SVC) was used to transmit real-time ultrasound video streams over each of the wireless links to observe the image quality as well as the diagnostic value of the received video stream. The information gathered during both testing phases revealed the abilities and limitations of the different wireless technologies. The results from the performance testing will be valuable in the future for those trying to develop network applications for telemedicine procedures over these wireless telecommunication options. Additionally, the testing demonstrated that the system is currently capable of using H.264 SVC compression to transmit VGA quality ultrasound video at 30 frames per second (fps) over 802.11g while QVGA resolution at frame rates between 10 and 15 fps is possible over 3G and satellite networks

M-health review: joining up healthcare in a wireless world

In recent years, there has been a huge increase in the use of information and communication technologies (ICT) to deliver health and social care. This trend is bound to continue as providers (whether public or private) strive to deliver better care to more people under conditions of severe budgetary constraint

Development of a portable 3D ultrasound imaging system for musculoskeletal tissues

Author name used in this publication: Q. H. HuangAuthor name used in this publication: Y. P. ZhengAuthor name used in this publication: M. H. LuAuthor name used in this publication: Z. R. ChiCentre for Signal Processing, Department of Electronic and Information EngineeringRehabilitation Engineering Centre2004-2005 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Evaluating a Web-Based Interface for Internet Telemedicine

The objective is to introduce the usability engineering methodology, heuristic evaluation, to the design and development of a web-based telemedicine system. Using a set of usability criteria, or heuristics, one evaluator examined the Spacebridge to Russia web-site for usability problems. Thirty-four usability problems were found in this preliminary study and all were assigned a severity rating. The value of heuristic analysis in the iterative design of a system is shown because the problems can be fixed before deployment of a system and the problems are of a different nature than those found by actual users of the system. It was therefore determined that there is potential value of heuristic evaluation paired with user testing as a strategy for optimal system performance design

Hybrid Region-based Image Compression Scheme for Mamograms and Ultrasound Images

The need for transmission and archive of mammograms and ultrasound Images has dramatically increased in tele-healthcare applications. Such images require large amount of' storage space which affect transmission speed. Therefore an effective compression scheme is essential. Compression of these images. in general. laces a great challenge to compromise between the higher compression ratio and the relevant diagnostic information. Out of the many studied compression schemes. lossless . IPl. (i- LS and lossy SPII IT are found to he the most efficient ones. JPEG-LS and SI'll IT are chosen based on a comprehensive experimental study carried on a large number of mammograms and ultrasound images of different sizes and texture. The lossless schemes are evaluated based on the compression ratio and compression speed. The distortion in the image quality which is introduced by lossy methods evaluated based on objective criteria using Mean Square Error (MSE) and Peak signal to Noise Ratio (PSNR). It is found that lossless compression can achieve a modest compression ratio 2: 1 - 4: 1. bossy compression schemes can achieve higher compression ratios than lossless ones but at the price of the image quality which may impede diagnostic conclusions. In this work, a new compression approach called Ilvbrid Region-based Image Compression Scheme (IIYRICS) has been proposed for the mammograms and ultrasound images to achieve higher compression ratios without compromising the diagnostic quality. In I LYRICS, a modification for JPI; G-LS is introduced to encode the arbitrary shaped disease affected regions. Then Shape adaptive SPIT IT is applied on the remaining non region of interest. The results clearly show that this hybrid strategy can yield high compression ratios with perfect reconstruction of diagnostic relevant regions, achieving high speed transmission and less storage requirement. For the sample images considered in our experiment, the compression ratio increases approximately ten times. However, this increase depends upon the size of the region of interest chosen. It is also föund that the pre-processing (contrast stretching) of region of interest improves compression ratios on mammograms but not on ultrasound images

Developing a mHealth-based portable ultrasound platform for breast cancer screening

Background Breast cancer is amongst the 10 most common cancers globally. The disease burden is increasing rapidly in Sub-Saharan African countries, where women living in rural and or remote areas are particularly prone to be diagnosed with late-stage breast cancer. This is due to the limited availability of advanced screening and diagnostic options. Ultrasound is a feasible screening tool for breast cancer, due to its portability, affordability and accuracy. The integration of mHealth with portable ultrasound enables the provision of screening services in rural and remote areas, through electronic consultation by a non-specialist with a specialist for interpretation and reporting of the ultrasound results. This project developed an application for a mHealth-based portable ultrasound platform that could be used by a non-specialist to provide breast cancer screening services with remote specialist support. Methods A systematic review of the literature was conducted for the period of 2004 to 2019 to gather evidence on the use of mHealth-based portable ultrasound platforms for improved access to ultrasound services like breast cancer screening. The evidence from the literature was used to design and develop a prototype of an application for a mHealth-based portable ultrasound platform suitable for breast cancer screening. The prototype application was integrated with a mobile-based portable ultrasound from Philips Lumify. Images generated by scanning a phantom breast using the portable ultrasound were uploaded onto the application and downloaded from the application to demonstrate the concept. Results The systematic review showed only two clinical conditions (obstetrics and cardiovascular disease) which used a mHealth-based portable ultrasound platform. The outcomes from the studies showed improved access to the respective ultrasound services in terms of patient management, early detection, improved quality of care and increased patient attendance, which resulted in access to other services. The integration of the prototype application with a mobile-based portable ultrasound resulted into a mHealthbased portable ultrasound platform prototype intended for breast cancer screening. The ability to upload images onto the platform and download images from the platform satisfied the design requirements for the platform. Conclusion A mHealth-based portable ultrasound prototype was developed, which has potential for improving access to breast cancer screening services. Further research including testing of the application with health professionals and patients is recommended to strengthen the feasibility of the concept

FPUS23: An Ultrasound Fetus Phantom Dataset with Deep Neural Network Evaluations for Fetus Orientations, Fetal Planes, and Anatomical Features

Ultrasound imaging is one of the most prominent technologies to evaluate the growth, progression, and overall health of a fetus during its gestation. However, the interpretation of the data obtained from such studies is best left to expert physicians and technicians who are trained and well-versed in analyzing such images. To improve the clinical workflow and potentially develop an at-home ultrasound-based fetal monitoring platform, we present a novel fetus phantom ultrasound dataset, FPUS23, which can be used to identify (1) the correct diagnostic planes for estimating fetal biometric values, (2) fetus orientation, (3) their anatomical features, and (4) bounding boxes of the fetus phantom anatomies at 23 weeks gestation. The entire dataset is composed of 15,728 images, which are used to train four different Deep Neural Network models, built upon a ResNet34 backbone, for detecting aforementioned fetus features and use-cases. We have also evaluated the models trained using our FPUS23 dataset, to show that the information learned by these models can be used to substantially increase the accuracy on real-world ultrasound fetus datasets. We make the FPUS23 dataset and the pre-trained models publicly accessible at https://github.com/bharathprabakaran/FPUS23, which will further facilitate future research on fetal ultrasound imaging and analysis