2.50
Hdl Handle:
http://hdl.handle.net/10547/336985
Title:
Parallel centerline extraction on the GPU
Authors:
Liu, Baoquan; Telea, Alexandru C.; Roerdink, Jos B.T.M.; Clapworthy, Gordon J.; Williams, David; Yang, Po; Dong, Feng; Codreanu, Valeriu; Chiarini, Alessandro
Abstract:
Centerline extraction is important in a variety of visualization applications including shape analysis, geometry processing, and virtual endoscopy. Centerlines allow accurate measurements of length along winding tubular structures, assist automatic virtual navigation, and provide a path-planning system to control the movement and orientation of a virtual camera. However, efficiently computing centerlines with the desired accuracy has been a major challenge. Existing centerline methods are either not fast enough or not accurate enough for interactive application to complex 3D shapes. Some methods based on distance mapping are accurate, but these are sequential algorithms which have limited performance when running on the CPU. To our knowledge, there is no accurate parallel centerline algorithm that can take advantage of modern many-core parallel computing resources, such as GPUs, to perform automatic centerline extraction from large data volumes at interactive speed and with high accuracy. In this paper, we present a new parallel centerline extraction algorithm suitable for implementation on a GPU to produce highly accurate, 26-connected, one-voxel-thick centerlines at interactive speed. The resulting centerlines are as accurate as those produced by a state-of-the-art sequential CPU method [40], while being computed hundreds of times faster. Applications to fly through path planning and virtual endoscopy are discussed. Experimental results demonstrating centeredness, robustness and efficiency are presented.
Affiliation:
University of Bedfordshire; University of Groningen; Eindhoven University of Technology; SCS srl, Italy
Citation:
Liu, B., Telea, A.C., Roerdink, J.B.T.M., Clapworthy, G.J., Williams, D., Yang, P., Dong, F., Codreanu, V., Chiarini, A., (2014) 'Parallel centerline extraction on the GPU', Computers & Graphics, 41 (6) pp 72-83
Publisher:
Elsevier
Journal:
Computers & Graphics
Issue Date:
Jun-2014
URI:
http://hdl.handle.net/10547/336985
DOI:
10.1016/j.cag.2014.02.003
Additional Links:
http://linkinghub.elsevier.com/retrieve/pii/S0097849314000272
Type:
Article
Language:
en
ISSN:
0097-8493
Appears in Collections:
Centre for Computer Graphics and Visualisation (CCGV)

Full metadata record

DC FieldValue Language
dc.contributor.authorLiu, Baoquanen
dc.contributor.authorTelea, Alexandru C.en
dc.contributor.authorRoerdink, Jos B.T.M.en
dc.contributor.authorClapworthy, Gordon J.en
dc.contributor.authorWilliams, Daviden
dc.contributor.authorYang, Poen
dc.contributor.authorDong, Fengen
dc.contributor.authorCodreanu, Valeriuen
dc.contributor.authorChiarini, Alessandroen
dc.date.accessioned2014-12-09T12:25:06Z-
dc.date.available2014-12-09T12:25:06Z-
dc.date.issued2014-06-
dc.identifier.citationLiu, B., Telea, A.C., Roerdink, J.B.T.M., Clapworthy, G.J., Williams, D., Yang, P., Dong, F., Codreanu, V., Chiarini, A., (2014) 'Parallel centerline extraction on the GPU', Computers & Graphics, 41 (6) pp 72-83en
dc.identifier.issn0097-8493-
dc.identifier.doi10.1016/j.cag.2014.02.003-
dc.identifier.urihttp://hdl.handle.net/10547/336985-
dc.description.abstractCenterline extraction is important in a variety of visualization applications including shape analysis, geometry processing, and virtual endoscopy. Centerlines allow accurate measurements of length along winding tubular structures, assist automatic virtual navigation, and provide a path-planning system to control the movement and orientation of a virtual camera. However, efficiently computing centerlines with the desired accuracy has been a major challenge. Existing centerline methods are either not fast enough or not accurate enough for interactive application to complex 3D shapes. Some methods based on distance mapping are accurate, but these are sequential algorithms which have limited performance when running on the CPU. To our knowledge, there is no accurate parallel centerline algorithm that can take advantage of modern many-core parallel computing resources, such as GPUs, to perform automatic centerline extraction from large data volumes at interactive speed and with high accuracy. In this paper, we present a new parallel centerline extraction algorithm suitable for implementation on a GPU to produce highly accurate, 26-connected, one-voxel-thick centerlines at interactive speed. The resulting centerlines are as accurate as those produced by a state-of-the-art sequential CPU method [40], while being computed hundreds of times faster. Applications to fly through path planning and virtual endoscopy are discussed. Experimental results demonstrating centeredness, robustness and efficiency are presented.en
dc.language.isoenen
dc.publisherElsevieren
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S0097849314000272en
dc.rightsArchived with thanks to Computers & Graphicsen
dc.subjectcenterlineen
dc.subjectparallel algorithmen
dc.subjectGPU techniquesen
dc.subjectvirtual endoscopyen
dc.titleParallel centerline extraction on the GPUen
dc.typeArticleen
dc.contributor.departmentUniversity of Bedfordshireen
dc.contributor.departmentUniversity of Groningenen
dc.contributor.departmentEindhoven University of Technologyen
dc.contributor.departmentSCS srl, Italyen
dc.identifier.journalComputers & Graphicsen
All Items in UOBREP are protected by copyright, with all rights reserved, unless otherwise indicated.