Implementation of diagnostically driven compression algorithms via WebRTC for IoT enabled tele-sonography

R, Bharath and Vaish, P and P, Rajalakshmi (2016) Implementation of diagnostically driven compression algorithms via WebRTC for IoT enabled tele-sonography. In: IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES), 4-8 Dec. 2016.

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In this paper, we have proposed novel framework for compressing the ultrasound images for IoT enabled telesonography. In ultrasound images, the diagnostic information is constrained to a particular region in the image, and sonographers look for that particular region for doing diagnosis. Therefore, by transmitting only that particular region to the remote sonographer, a significant compression can be achieved. Diagnostic information present in an image is organ specific, hence we came up with a framework to detect the organs and compress accordingly. We developed automated, semi-automated and manual algorithms for detecting the organs in an image. The automated and semi-automated algorithms for organ detection are based on Viola Jones and active shape model respectively. The detected organ is JPEG compressed and transmitted to remote sonographer through WebRTC technology. WebRTC enables direct browser-to-browser connection enabling fast and secure transmission of data. Organ detection algorithms are implemented through WebRTC and hence there is no need to install any softwares at the end devices. With the proposed framework, any ultrasound scanner can access service from the server, compress it and transmit to the expert end. The remote sonographer from anywhere can connect to the ultrasound scanner with his laptop, mobile, tablet etc., for doing diagnosis. The performance of proposed framework is evaluated by computing the compression efficiency on ten kidney ultrasound images.

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IITH Creators:
IITH CreatorsORCiD
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Ultrasonic imaging, Shape, WebRTC, Image coding, Kidney, Image segmentation
Subjects: Others > Electricity
Divisions: Department of Electrical Engineering
Depositing User: Team Library
Date Deposited: 13 Feb 2017 09:05
Last Modified: 13 Feb 2017 09:05
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