Abstract
Recently, telemedicine has been widely applied in remote diagnosis, treatment and counseling, where the Internet of Things (IoT) technology plays an important role. In the process of telemedicine, data are collected from remote medical equipment, such as CT machine and MRI machine, and then transmitted and reconstructed locally in three-dimensions. Due to the large amount of data to be transmitted in the reconstructed model and the small storage capacity, data need to be compressed progressively before transmission. On this basis, we proposed a lightweight progressive transmission algorithm based on large data visualization in telemedicine to improve transmission efficiency and achieve lossless transmission of original data. Moreover, a novel four-layer system architecture based on IoT has been introduced, including the sensing layer, analysis layer, network layer and application layer. In this way, the three-dimensional reconstructed data at the local end is compressed and transmitted to the remote end, and then visualized at the remote end to show reconstructed 3D models. Thus, it is conducive to doctors in remote real-time diagnosis and treatment, and then realize the data processing and transmission between doctors, patients and medical equipment.
Highlights
Internet of Things (IoT) has been widely applied in information technology (IT) which is a concept of connecting physical objects via networks for data collection and sharing
Medical IoT is considered as a basis of connected health, where the data exchanging is achieved among doctors, patients and medical equipment [7]
To solve the problem above, we proposed an IoT-based framework of lightweight progressive coding to visualize medical big data, where both a lightweight progressive transmission method and a four-layered system architecture are proposed
Summary
Internet of Things (IoT) has been widely applied in information technology (IT) which is a concept of connecting physical objects via networks for data collection and sharing. G. Xu et al.: IoT-Based Framework of Webvr Visualization for Medical Big Data in Connected Health. The medical big data is defined as a collection based on health-related data which is produced in the entire diagnosis process, from clinic registration to hospital follow-up of patients [9], [10]. To solve the problem above, we proposed an IoT-based framework of lightweight progressive coding to visualize medical big data, where both a lightweight progressive transmission method and a four-layered system architecture are proposed. The lossless medical visualization can be transmitted from local to the mobile remote end, contributing to a more accurate disease diagnosis.
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