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ViviSection: Skeleton-based Volume Editing.

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Title: ViviSection: Skeleton-based Volume Editing.
Authors: Karimov, A.1, Mistelbauer, G.1, Schmidt, J.1, Mindek, P.1, Schmidt, E.2, Sharipov, T.3, Bruckner, S.4, Gröller, E.1
Source: Computer Graphics Forum. Dec2013, Vol. 32 Issue 3pt4, p461-470. 10p. 6 Color Photographs, 3 Charts.
Subjects: Product usage segmentation, Image segmentation, Image quality in imaging systems, Computer graphics, Data extraction, Feature extraction, Confirmation (Logic)
Abstract: Volume segmentation is important in many applications, particularly in the medical domain. Most segmentation techniques, however, work fully automatically only in very restricted scenarios and cumbersome manual editing of the results is a common task. In this paper, we introduce a novel approach for the editing of segmentation results. Our method exploits structural features of the segmented object to enable intuitive and robust correction and verification. We demonstrate that our new approach can significantly increase the segmentation quality even in difficult cases such as in the presence of severe pathologies. [ABSTRACT FROM AUTHOR]
Copyright of Computer Graphics Forum is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: ViviSection: Skeleton-based Volume Editing.
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  Data: <searchLink fieldCode="JN" term="%22Computer+Graphics+Forum%22">Computer Graphics Forum</searchLink>. Dec2013, Vol. 32 Issue 3pt4, p461-470. 10p. 6 Color Photographs, 3 Charts.
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  Data: <searchLink fieldCode="DE" term="%22Product+usage+segmentation%22">Product usage segmentation</searchLink><br /><searchLink fieldCode="DE" term="%22Image+segmentation%22">Image segmentation</searchLink><br /><searchLink fieldCode="DE" term="%22Image+quality+in+imaging+systems%22">Image quality in imaging systems</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+graphics%22">Computer graphics</searchLink><br /><searchLink fieldCode="DE" term="%22Data+extraction%22">Data extraction</searchLink><br /><searchLink fieldCode="DE" term="%22Feature+extraction%22">Feature extraction</searchLink><br /><searchLink fieldCode="DE" term="%22Confirmation+%28Logic%29%22">Confirmation (Logic)</searchLink>
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  Data: Volume segmentation is important in many applications, particularly in the medical domain. Most segmentation techniques, however, work fully automatically only in very restricted scenarios and cumbersome manual editing of the results is a common task. In this paper, we introduce a novel approach for the editing of segmentation results. Our method exploits structural features of the segmented object to enable intuitive and robust correction and verification. We demonstrate that our new approach can significantly increase the segmentation quality even in difficult cases such as in the presence of severe pathologies. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Computer Graphics Forum is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1111/cgf.12133
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      – Code: eng
        Text: English
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        PageCount: 10
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      – SubjectFull: Product usage segmentation
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      – SubjectFull: Image segmentation
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      – SubjectFull: Image quality in imaging systems
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      – SubjectFull: Computer graphics
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      – SubjectFull: Data extraction
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      – SubjectFull: Feature extraction
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      – SubjectFull: Confirmation (Logic)
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      – TitleFull: ViviSection: Skeleton-based Volume Editing.
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              Text: Dec2013
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              Y: 2013
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