Dynamic Reconstruction of Deformable Soft-Tissue with Stereo Scope in Minimal Invasive Surgery

Song, J; Wang, J; Zhao, L; Huang, S; Dissanayake, G

Dynamic Reconstruction of Deformable Soft-Tissue with Stereo Scope in Minimal Invasive Surgery

Song, J Wang, J Zhao, L

Huang, S

Dissanayake, G

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Publication Type:: Journal Article
Citation:: IEEE Robotics and Automation Letters, 2018, 3 (1), pp. 155 - 162
Issue Date:: 2018-01-01

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Field	Value	Language
dc.contributor.author	Song, J	en_US
dc.contributor.author	Wang, J	en_US
dc.contributor.author	Zhao, L https://orcid.org/0000-0003-4063-8183	en_US
dc.contributor.author	Huang, S https://orcid.org/0000-0002-6124-4178	en_US
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680	en_US
dc.date.issued	2018-01-01	en_US
dc.identifier.citation	IEEE Robotics and Automation Letters, 2018, 3 (1), pp. 155 - 162	en_US
dc.identifier.uri	http://hdl.handle.net/10453/118112
dc.description.abstract	© 2016 IEEE. In minimal invasive surgery, it is important to rebuild and visualize the latest deformed shape of soft-tissue surfaces to mitigate tissue damages. This letter proposes an innovative Simultaneous localization and mapping (SLAM) algorithm for deformable dense reconstruction of surfaces using a sequence of images from a stereoscope. We introduce a warping field based on the embedded deformation nodes with three-dimensional (3-D) shapes recovered from consecutive pairs of stereo images. The warping field is estimated by deforming the last updated model to the current live model. Our SLAM system can incrementally build a live model by progressively fusing new observations with vivid accurate texture; estimate the deformed shape of unobserved region with the principle as-rigid-as-possible; show the consecutive shape of models; and estimate the current relative pose between the soft-tissue and the scope. In-vivo experiments with publicly available datasets demonstrate that the 3-D models can be incrementally built for different soft-tissues with different deformations from sequences of stereo images obtained by laparoscopes. Results show the potential clinical application of our SLAM system for providing surgeon useful shape and texture information in minimal invasive surgery.	en_US
dc.relation.ispartof	IEEE Robotics and Automation Letters	en_US
dc.relation.isbasedon	10.1109/LRA.2017.2735487	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Dynamic Reconstruction of Deformable Soft-Tissue with Stereo Scope in Minimal Invasive Surgery	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	3	en_US
utslib.for	1004 Medical Biotechnology	en_US
utslib.for	0913 Mechanical Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	closed_access	*
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	3	en_US

Abstract:

© 2016 IEEE. In minimal invasive surgery, it is important to rebuild and visualize the latest deformed shape of soft-tissue surfaces to mitigate tissue damages. This letter proposes an innovative Simultaneous localization and mapping (SLAM) algorithm for deformable dense reconstruction of surfaces using a sequence of images from a stereoscope. We introduce a warping field based on the embedded deformation nodes with three-dimensional (3-D) shapes recovered from consecutive pairs of stereo images. The warping field is estimated by deforming the last updated model to the current live model. Our SLAM system can incrementally build a live model by progressively fusing new observations with vivid accurate texture; estimate the deformed shape of unobserved region with the principle as-rigid-as-possible; show the consecutive shape of models; and estimate the current relative pose between the soft-tissue and the scope. In-vivo experiments with publicly available datasets demonstrate that the 3-D models can be incrementally built for different soft-tissues with different deformations from sequences of stereo images obtained by laparoscopes. Results show the potential clinical application of our SLAM system for providing surgeon useful shape and texture information in minimal invasive surgery.

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http://hdl.handle.net/10453/118112