Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-34778-8_50
Title: Histopathology image streaming
Authors: Mohanty, M.
Ooi, W.T. 
Keywords: CABAC
CAVLC
Histopathology Image
Packetization
Predictive Image Compression
WebP
Issue Date: 2012
Source: Mohanty, M.,Ooi, W.T. (2012). Histopathology image streaming. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7674 LNCS : 534-545. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-34778-8_50
Abstract: This paper proposes an image streaming framework to stream histopathology image of a patient over a lossy network. Firstly, the large histopathology image is divided into a number of fixed size tiles to facilitate ROI-based streaming. Secondly, each tile is compressed using a variant of WebP so that the size of the compressed data is 20% to 30% less than the size of the compressed data when the same tile is compressed using JPEG. Finally, a greedy packetization scheme is proposed to pack the inter-dependent macroblocks of any compressed tile so that the client is able to decode more number of macroblocks than the naive method at any intermediate stage of streaming. © 2012 Springer-Verlag.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/41661
ISBN: 9783642347771
ISSN: 03029743
DOI: 10.1007/978-3-642-34778-8_50
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