Multiple transmission optimization of medical images in recourse-constraint mobile telemedicine systems. (July 2017)

• Record Type: Journal Article
• Authors: Jiang, Nan; Zhuang, Yi; Chiu, Dickson K.W.
• Is Part Of: Computer methods and programs in biomedicine. Volume 145(2017)
• Page Start: 103
• Page End: 113
• Publication Date: 2017-07
• Subjects: Medical image -- Multi-resolution -- Mobile telemedicine system -- Batch transmission; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2017.04.002
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: A concurrent transmission platform for multiple medical images. Transmission performance improvement from a perspective of the batch transmission processing. Cost-aware multiple transmission requests grouping. Adaptive adjustment of the pixel resolutions of image block replicas. Abstract: Background and objective: In the state-of-the-art image transmission methods, multiple large medical images are usually transmitted one by one which is very inefficient. The objective of our study is to devise an effective and efficient multiple transmission optimization scheme for medical images called Mt o via analyzing the visual content of the multiple images based on the characteristics of a recourse-constraint mobile telemedicine system ( MTS ) and the medical images; Methods: To better facilitate the efficient Mto processing, two enabling techniques, i.e., 1) NIB grouping scheme, and 2) adaptive RIB replicas selection are developed. Given a set of transmission images (Ω), the correlation of these transmission images is first explored, the pixel resolutions of the corresponding MIB s keep high, the NIB s are grouped into k clusters based on the visual similarity in which the k RIB s are obtained. An optimal pixel resolution for the RIB s is derived based on the current network bandwidth and their corresponding areas, etc. Then, the candidate MIB s and the k RIB s are transmitted to the receiver node based on their transmission priorities. Finally, the IB s are reconstructed and displayed at the receiver node level for different users. Results: The experimental results show that our approach is about 45% more efficient than the state-of-the-art methods, significantly minimizing the response time by decreasing the network communication cost while improving the transmission throughput; Conclusions: Our proposed Mto method can be seamlessly applied in a recourse-constraint MTS environment in which the high transmission efficiency and the acceptable image quality can be guaranteed.