Pub Date : 2013-07-14DOI: 10.1109/ICWAPR.2013.6599284
Peng Wang, Bin Fang, Yi Wang, Jingrui Pi
The three-dimensional reconstruction of the liver images and to establish a virtual liver model is a way to compensate for the weaknesses of the two-dimensional images evaluation. The structure of vasculature describes the anatomic location and hierarchy of vessels, also embodies the blood supply. To get the graph representation of virtual hepatic vascular tree, we present a pipeline of algorithm steps. Firstly we extract the centerline of hepatic vasculature and execute the pruning operation, then we identify the branch-points and traverse the skeleton, and build the graph representation with a trie tree at the same time. These algorithm steps have been applied to the virtual liver surgery planning system and works well, and we can calculate some parameters such as vessel length, volume and diameter, and partition the liver interactively, and with these surgeons are able to analyze the vasculature quantitatively.
{"title":"3D topological construction model of hepatic vascular tree in CT angiography","authors":"Peng Wang, Bin Fang, Yi Wang, Jingrui Pi","doi":"10.1109/ICWAPR.2013.6599284","DOIUrl":"https://doi.org/10.1109/ICWAPR.2013.6599284","url":null,"abstract":"The three-dimensional reconstruction of the liver images and to establish a virtual liver model is a way to compensate for the weaknesses of the two-dimensional images evaluation. The structure of vasculature describes the anatomic location and hierarchy of vessels, also embodies the blood supply. To get the graph representation of virtual hepatic vascular tree, we present a pipeline of algorithm steps. Firstly we extract the centerline of hepatic vasculature and execute the pruning operation, then we identify the branch-points and traverse the skeleton, and build the graph representation with a trie tree at the same time. These algorithm steps have been applied to the virtual liver surgery planning system and works well, and we can calculate some parameters such as vessel length, volume and diameter, and partition the liver interactively, and with these surgeons are able to analyze the vasculature quantitatively.","PeriodicalId":236156,"journal":{"name":"2013 International Conference on Wavelet Analysis and Pattern Recognition","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124273315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-14DOI: 10.1109/ICWAPR.2013.6599327
Yubei Lin, Xing-Ming Zhang
Video coding plays a more and more important role when vast amount of multimedia data are emerging. Traditional video compression methods take into account the statistical redundancy among pixels when encoding videos. Since the human eyes are the ultimate receivers of visual information, considering the perception of the human visual system (HVS) may help to reach higher compression ratio. Perceptual video coding, which aims to remove the perceptual redundancy of encoded videos, has attracted more and more awareness. In this paper, recent developments in perceptual video coding are reviewed, The current perceptual-based approaches are classified into five categories, each with the principle of the methods, the applications as well as the problems. Key-issues are then discussed, which indicate that there remains much potential to exploit in perceptual video coding.
{"title":"Recent developments in perceptual video coding","authors":"Yubei Lin, Xing-Ming Zhang","doi":"10.1109/ICWAPR.2013.6599327","DOIUrl":"https://doi.org/10.1109/ICWAPR.2013.6599327","url":null,"abstract":"Video coding plays a more and more important role when vast amount of multimedia data are emerging. Traditional video compression methods take into account the statistical redundancy among pixels when encoding videos. Since the human eyes are the ultimate receivers of visual information, considering the perception of the human visual system (HVS) may help to reach higher compression ratio. Perceptual video coding, which aims to remove the perceptual redundancy of encoded videos, has attracted more and more awareness. In this paper, recent developments in perceptual video coding are reviewed, The current perceptual-based approaches are classified into five categories, each with the principle of the methods, the applications as well as the problems. Key-issues are then discussed, which indicate that there remains much potential to exploit in perceptual video coding.","PeriodicalId":236156,"journal":{"name":"2013 International Conference on Wavelet Analysis and Pattern Recognition","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115247576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-01DOI: 10.1109/ICWAPR.2013.6599326
Guangyi Chen, S. Krishnan, W. Xie
The wavelet transform is a very useful tool for a number of real-life applications. This is due to its multiresolution representation of signals and its localized time-frequency property. The Ramanujan sums (RS) were introduced to signal processing recently. The RS are orthogonal in nature and therefore offer excellent energy conservation. The RS operate on integers and hence can obtain a reduced quantization error implementation. In this paper, we combine the wavelet transform with the RS transform in order to create a new representation of signals. We are trying to combine the merits of the both transforms and at the same time overcome their shortcomings. Our proposed transform contains much richer features than the wavelet transform, so it could be useful for such applications as time-frequency analysis, pattern recognition and image analysis.
{"title":"Ramanujan sums-wavelet transform for signal analysis","authors":"Guangyi Chen, S. Krishnan, W. Xie","doi":"10.1109/ICWAPR.2013.6599326","DOIUrl":"https://doi.org/10.1109/ICWAPR.2013.6599326","url":null,"abstract":"The wavelet transform is a very useful tool for a number of real-life applications. This is due to its multiresolution representation of signals and its localized time-frequency property. The Ramanujan sums (RS) were introduced to signal processing recently. The RS are orthogonal in nature and therefore offer excellent energy conservation. The RS operate on integers and hence can obtain a reduced quantization error implementation. In this paper, we combine the wavelet transform with the RS transform in order to create a new representation of signals. We are trying to combine the merits of the both transforms and at the same time overcome their shortcomings. Our proposed transform contains much richer features than the wavelet transform, so it could be useful for such applications as time-frequency analysis, pattern recognition and image analysis.","PeriodicalId":236156,"journal":{"name":"2013 International Conference on Wavelet Analysis and Pattern Recognition","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114669219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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