對於遠距醫療應用上使用階層式層級樹狀結構分組之可調式醫學資料壓縮與傳送

Scalable Medical Data Compression and Transmission Using Layered Set Partitioning in Hierarchical Trees Transform for Telemedicine Applications

李國榮(Kuo-Jung Li)

指導教授 ： 黃文吉

中原大學/工學院/電機工程研究所/碩士(2001年)

https://doi.org/10.6840/cycu200100050

摘要

本篇論文在對於遠距醫療應用上提出一個優越的醫學資料壓縮法則，稱之為階層式層級樹狀結構分組演算法。我們能夠藉著實現這個演算法有效的減少遠距醫療應用上通訊網路的複雜度，以及實現整個架構上所花費的成本。
基於不同應用上成本效應的考量，遠距醫療系統上的裝置可能變化非常廣泛。不同的顯示或處理裝置對於傳送器或編碼器所傳送的訊號，可能個自在訊雜比與解析度上有不同的需求。這問題的一個解決方法是使用同時播放技術，將各個裝置所要求的資料均獨自編碼與傳送。這種方式將會要求更多的硬碟空間與處理資料所須之系統資源。
而可調式的傳輸方式能夠被用來解決這類問題。本篇論文對於可調式傳輸方式設計上使用階層式層級樹狀結構分組演算法(LSPIHT)。在LSPIHT演算法中，我們將一個已編碼的資料流分成兩層或更多層。相對於每一階層的壓縮比與解析度能在編碼前事先規劃，在接收端醫學訊號可以藉由解碼資料流，從最基層累增至不同的更高層，而重建出不同訊雜比或解析度的訊號。因此，對於有不同要求的使用者，能藉由共享相同的傳輸系統而達到減少來源編碼負擔的目的。
經由模擬結果顯示，相較於SPIHT與其他資料壓縮技術，LSPIHT演算法在對每一階層要求較少的資源與花費的情況中，能有較佳的重建表現。

關鍵字

遠距醫療 ； 小波轉換 ； 同時播放 ； 可調式傳輸

並列摘要

In this thesis, a novel medical data compression algorithm, termed layered set partitioning in hierarchical trees (LSPIHT) algorithm, is presented for telemedicine applications. By implementing the algorithm, we can effectively reduce the complexity of the telecommunication networks for telemedicine applications and the costs for realizing the infrastructure.
Because of the cost-effectiveness consideration of different applications, the equipments of a telemedicine system may vary widely. Different displaying or processing devices may have distinct demands on the signal-to-noise ratio and/or resolution of the reconstructed data delivered from a transmitter or source encoder. One solution is to use the simulcast technique where medical data is encoded and delivered independently for each of the device. This approach requires more resources to be used in the encoder in terms of disk space and management overhead.
The scalable transmission scheme can be used to solve these problems. This thesis employs a layered SPIHT technique for the design of scalable transmission systems. In the LSPIHT, an encoded bit stream can be delivered in tow or more layers. The compression ratio (CR) and resolution associated with each layer can be pre-specified before encoding. At the receiving ends, medical data are reconstructed by decoding bit stream accumulated up to different enhancement layers from the base layer. Users with various SNR and resolution requirements therefore can share the same source encoder and transmission system.
Simulation results show that, as compared with SPIHT algorithm and other data compression techniques, the LSPIHT algorithm attains better rate-distortion performance for the encoding of each layer while demanding less resources and costs.

並列關鍵字

Telemedicine ； SPIHT ； Simulcast Technique ； Scalable Transmission

參考文獻

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