2.50
Hdl Handle:
http://hdl.handle.net/10547/250932
Title:
Accumulation of local maximum intensity for feature enhanced volume rendering
Authors:
Liang, Ronghua; Wu, Yunfei; Dong, Feng; Clapworthy, Gordon J.
Abstract:
Maximum Intensity Difference Accumulation (MIDA) combines the advantage of Direct Volume Rendering (DVR) and Maximum Intensity Projection (MIP). However, many features with local maximum intensity are still missing in the final rendering image. This paper presents a novel approach to focus on features with local maximum intensity within the dataset. Moving Least Squares (MLS) is used to smooth each ray profile during the raycasting in order to eliminate noise in the data and to highlight significant transition points on the profile. We then adopt a local minimum-point searching method to analyze the ray profile, and identify the transition points that mark the local maximum intensity points within the dataset. At the rendering stage, we implement a novel local intensity difference accumulation (LIDA) to accumulate the colors and opacity. Surface shading is introduced to improve the spatial cues of the features. We also employ tone-reduction to preserve the original local contrast. Our approach can highlight local features in the dataset without involving the adjustment of transfer functions. The experiments demonstrate high-quality rendering results at an interactive frame rate.
Citation:
Accumulation of local maximum intensity for feature enhanced volume rendering 2012, 28 (6-8):625-633 The Visual Computer
Publisher:
Springer
Journal:
The Visual Computer
Issue Date:
Jun-2012
URI:
http://hdl.handle.net/10547/250932
DOI:
10.1007/s00371-012-0680-5
Additional Links:
http://www.springerlink.com/index/10.1007/s00371-012-0680-5
Type:
Article
Language:
en
ISSN:
0178-2789; 1432-2315
Appears in Collections:
Centre for Computer Graphics and Visualisation (CCGV)

Full metadata record

DC FieldValue Language
dc.contributor.authorLiang, Ronghuaen_GB
dc.contributor.authorWu, Yunfeien_GB
dc.contributor.authorDong, Fengen_GB
dc.contributor.authorClapworthy, Gordon J.en_GB
dc.date.accessioned2012-11-05T09:27:52Z-
dc.date.available2012-11-05T09:27:52Z-
dc.date.issued2012-06-
dc.identifier.citationAccumulation of local maximum intensity for feature enhanced volume rendering 2012, 28 (6-8):625-633 The Visual Computeren_GB
dc.identifier.issn0178-2789-
dc.identifier.issn1432-2315-
dc.identifier.doi10.1007/s00371-012-0680-5-
dc.identifier.urihttp://hdl.handle.net/10547/250932-
dc.description.abstractMaximum Intensity Difference Accumulation (MIDA) combines the advantage of Direct Volume Rendering (DVR) and Maximum Intensity Projection (MIP). However, many features with local maximum intensity are still missing in the final rendering image. This paper presents a novel approach to focus on features with local maximum intensity within the dataset. Moving Least Squares (MLS) is used to smooth each ray profile during the raycasting in order to eliminate noise in the data and to highlight significant transition points on the profile. We then adopt a local minimum-point searching method to analyze the ray profile, and identify the transition points that mark the local maximum intensity points within the dataset. At the rendering stage, we implement a novel local intensity difference accumulation (LIDA) to accumulate the colors and opacity. Surface shading is introduced to improve the spatial cues of the features. We also employ tone-reduction to preserve the original local contrast. Our approach can highlight local features in the dataset without involving the adjustment of transfer functions. The experiments demonstrate high-quality rendering results at an interactive frame rate.en_GB
dc.language.isoenen
dc.publisherSpringeren_GB
dc.relation.urlhttp://www.springerlink.com/index/10.1007/s00371-012-0680-5en_GB
dc.rightsArchived with thanks to The Visual Computeren_GB
dc.titleAccumulation of local maximum intensity for feature enhanced volume renderingen
dc.typeArticleen
dc.identifier.journalThe Visual Computeren_GB
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