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|Title:||Histopathology image streaming|
Predictive Image Compression
|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)|
|Appears in Collections:||Staff Publications|
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