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Medical Image Processing Environment
Published in Jiří Jan, Medical Image Processing, Reconstruction and Analysis, 2019
Telemedicine, which can be roughly defined as providing medical care remotely, is crucially dependent on image communication and processing. Primarily, teleradiology—sending medical images of a patient to an expert at a distant place for evaluation—is one of the earliest components of telemedicine, besides the naturally easier remote evaluation of ECG and other signals. Sending video sequences in real time is essential in telesurgery, the most demanding field of telemedicine, where the surgeon acts indirectly, via a suitable interface (data gloves, etc.), a telecommunication link, and mechanical actuators, while tracking his action via a real-time video, possibly in high-resolution stereo vision, mediated by a reverse communication link. This may be denoted as telepresence of the surgeon. Obviously, both the physical distance and complexity of the duplex communication channel influence signal delay, which limits the maximum range of such a service. Again, the effective image processing, namely, the video data compression, is crucial for the success of the telepresence system. Image communication, with a possibility of experimental processing and analysis, also forms one of the pillars of teleeducation (distant electronic study) of some medical skills, which is also considered an important part of telemedicine.
Telehealth and Healthcare Team Communication
Published in Christopher P. Nemeth, Improving Healthcare Team Communication, 2017
Teleradiology has facilitated faster turnaround times for the interpretation of diagnostic images. This has been particularly beneficial for sites where there is no local radiologist or sporadic coverage or limited coverage at night. Teleradiology facilitates the electronic transfer of digital diagnostic images to a radiologist located at a distant site versus having to physically courier film images or a DVD/hard disk containing the images. This can speed up turnaround time for reporting and allow for urgent review of a case if necessary. A controversial practice that is becoming increasingly popular in developed countries is using teleradiology to transmit diagnostic images to radiologists in foreign countries for review. In the United States, hundreds of hospitals are sending their diagnostic images to foreign radiologists, in particular India, to review (Wachter 2006). The two major benefits of this service are: (1) fast turnaround time, and (2) decreased cost. Turnaround times are fast because images are sent during the evening/night in the USA, which is daytime in India, allowing Indian radiologists to review diagnostic images during regular office hours. A report is transmitted back to the USA and available the next morning. This service can also be less expensive, since radiologists in India are reimbursed at a lower rate than their American counterparts.
Audit of Artificial Intelligence Algorithms and Its Impact in Relieving Shortage of Specialist Doctors
Published in Sandeep Reddy, Artificial Intelligence, 2020
Vidur Mahajan, Vasanth Venugopal
Following teleradiology, the next technological advancement is touted to be artificial intelligence (AI). With globally about $448 million invested into start-ups as of June 2018 (Funding analysis, 2018), there is no denying that AI will come into the medical imaging domain and transform it. Through this chapter, we take a deep dive into commercially available AI-based technologies, those under research and those that, as far as published literature goes, are not currently being developed. We examine the potential impact each can have in addressing the problem of radiologists’ shortage in rural India.
Big data analytics in medical engineering and healthcare: methods, advances and challenges
Published in Journal of Medical Engineering & Technology, 2020
Lidong Wang, Cheryl Ann Alexander
The infrastructure of digital health data and electronic health records (EHR) has been used in achieving public health goals such as health-related research, healthcare delivery, population health surveillance and personal health management. Teleradiology and telemedicine systems facilitate healthcare delivery to both rural and urban patients alike. Personal health management can be supported by apps like Apple Health. Big data technologies have the potential to fulfil these goals and deliver quality services [1]. Personalised predictive analytics is an emerging method of healthcare delivery that relies on the similarity of patients; when a new patient needs treatment, similar patients are found from historical databases, insights are drawn from their records and personalised predictions are performed. For example, this method has been used in drug recommendation systems, identifying risk factors for similar patients, predicting heart failure according to telemonitoring data and fulfilling personalised medical treatment [2].