This Chapter presents an overview on the state-of-the-art in the ¯eld of medical image coding. After a brief description of the more representative 2-D and 3-D compression algorithms, a versatile model-based coding scheme for three-dimensional medical is introduced. The potential of the proposed system is due to the fact that it copes with many of the characteristic requirements of the medical imaging field without sacrificing the compression effciency. Among the most interesting features are progressively refinable up-to-lossless quality of the decoded information, object-based functionalities and the possibility to decode a single 2-D im- age of the dataset. Furthermore, such features can be combined enabling a swift access to any two-dimensional object of any image of interest with refinable quality. The price to pay is an overhead in the bitstream which slightly degrades the compression performance. Though, the possibility to focus the decoding process on a specific region of a certain 2-D image allows a very effcient access to the information of interest, which can be recovered with the desired up-to lossless quality. We believe this is an important feature for a coding system meant to be used for medical applications, which largely compensates for the eventual loss in compression that could be implied.
Trends in Model-Based Coding of Multidimensional Medical Data
MENEGAZ, Gloria
2006-01-01
Abstract
This Chapter presents an overview on the state-of-the-art in the ¯eld of medical image coding. After a brief description of the more representative 2-D and 3-D compression algorithms, a versatile model-based coding scheme for three-dimensional medical is introduced. The potential of the proposed system is due to the fact that it copes with many of the characteristic requirements of the medical imaging field without sacrificing the compression effciency. Among the most interesting features are progressively refinable up-to-lossless quality of the decoded information, object-based functionalities and the possibility to decode a single 2-D im- age of the dataset. Furthermore, such features can be combined enabling a swift access to any two-dimensional object of any image of interest with refinable quality. The price to pay is an overhead in the bitstream which slightly degrades the compression performance. Though, the possibility to focus the decoding process on a specific region of a certain 2-D image allows a very effcient access to the information of interest, which can be recovered with the desired up-to lossless quality. We believe this is an important feature for a coding system meant to be used for medical applications, which largely compensates for the eventual loss in compression that could be implied.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
