A wavelet-based region of interest encoder for the compression of angiogram video sequences
A new method for the compression of angiogram video sequences is presented. The method is based on the philosophy that diagnostically significant areas of the image should be allocated the greatest proportion of the total allocated bit budget. The approach uses a three-dimensional wavelet-coder base...
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| Veröffentlicht in: | IEEE journal of biomedical and health informatics 2004-06, Vol.8 (2), p.103-113 |
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| container_title | IEEE journal of biomedical and health informatics |
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| creator | Gibson, D. Spann, M. Woolley, S.I. |
| description | A new method for the compression of angiogram video sequences is presented. The method is based on the philosophy that diagnostically significant areas of the image should be allocated the greatest proportion of the total allocated bit budget. The approach uses a three-dimensional wavelet-coder based on the popular set partitioning in hierarchical trees algorithm. Incorporated into this framework are a region-of-interest (ROI) detection stage and a texture-modeling stage. The combined result is an approach that models the high-frequency wavelet coefficients for some diagnostically unimportant regions of the image in an extremely efficient manner. This allows additional bits to be used within the ROI to improve the quality of the diagnostically significant areas. Results are compared for a number of real data sets and evaluated by trained cardiologists. |
| doi_str_mv | 10.1109/TITB.2004.826722 |
| format | Article |
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The method is based on the philosophy that diagnostically significant areas of the image should be allocated the greatest proportion of the total allocated bit budget. The approach uses a three-dimensional wavelet-coder based on the popular set partitioning in hierarchical trees algorithm. Incorporated into this framework are a region-of-interest (ROI) detection stage and a texture-modeling stage. The combined result is an approach that models the high-frequency wavelet coefficients for some diagnostically unimportant regions of the image in an extremely efficient manner. This allows additional bits to be used within the ROI to improve the quality of the diagnostically significant areas. 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The method is based on the philosophy that diagnostically significant areas of the image should be allocated the greatest proportion of the total allocated bit budget. The approach uses a three-dimensional wavelet-coder based on the popular set partitioning in hierarchical trees algorithm. Incorporated into this framework are a region-of-interest (ROI) detection stage and a texture-modeling stage. The combined result is an approach that models the high-frequency wavelet coefficients for some diagnostically unimportant regions of the image in an extremely efficient manner. This allows additional bits to be used within the ROI to improve the quality of the diagnostically significant areas. 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| ispartof | IEEE journal of biomedical and health informatics, 2004-06, Vol.8 (2), p.103-113 |
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| subjects | Algorithms Angiography - methods Cardiology Compressing Coronary Angiography - methods Data Compression - methods Database Management Systems Discrete cosine transforms Encoders Extreme values Frequency estimation HDTV Humans Image coding Image Enhancement - methods Image Processing, Computer-Assisted - methods Information systems Mathematical models Motion estimation Movement Partitioning algorithms Pattern Recognition, Automated Reproducibility of Results Sensitivity and Specificity Signal Processing, Computer-Assisted Transform coding Video compression Video Recording - methods Video sequences |
| title | A wavelet-based region of interest encoder for the compression of angiogram video sequences |
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