Parameter measurement of 3D soft tissue model in warping simulation
Parameter measurement of 3D soft tissue model is of great theoretical significance and application value in virtual surgery training simulation system. To solve the problems of existing soft tissue parameter measurement methods with high complexity, we propose a fast and effective parameter measurem...
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| creator | Xiangyun Liao Weixin Si Zhaoliang Duan Xi Chen Jianhui Zhao Zhiyong Yuan |
| description | Parameter measurement of 3D soft tissue model is of great theoretical significance and application value in virtual surgery training simulation system. To solve the problems of existing soft tissue parameter measurement methods with high complexity, we propose a fast and effective parameter measurement method. We adopt a pillow as test material and exert pressure on it to simulate the parameter measurement of 3D soft tissue model in warping simulation. During the experiment, we construct a motion capture system with 3 cameras to obtain the warping set of the soft tissue model and carry out the 3D reconstruction of it by utilizing reverse engineering method. We obtain the pressure by using a miniature pressure sensor and calibrate the pressure sensor with BP (Back Propagation) neural network and then we calculate the 3D soft tissue parameter by using the pressure data and the 3D reconstruction result. The experimental results show that the parameter measurement method we proposed can obtain the parameter of 3D soft tissue model fast and effectively. |
| doi_str_mv | 10.1109/ICSAI.2012.6223216 |
| format | Conference Proceeding |
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To solve the problems of existing soft tissue parameter measurement methods with high complexity, we propose a fast and effective parameter measurement method. We adopt a pillow as test material and exert pressure on it to simulate the parameter measurement of 3D soft tissue model in warping simulation. During the experiment, we construct a motion capture system with 3 cameras to obtain the warping set of the soft tissue model and carry out the 3D reconstruction of it by utilizing reverse engineering method. We obtain the pressure by using a miniature pressure sensor and calibrate the pressure sensor with BP (Back Propagation) neural network and then we calculate the 3D soft tissue parameter by using the pressure data and the 3D reconstruction result. The experimental results show that the parameter measurement method we proposed can obtain the parameter of 3D soft tissue model fast and effectively.</description><identifier>ISBN: 9781467301985</identifier><identifier>ISBN: 1467301981</identifier><identifier>EISBN: 9781467301992</identifier><identifier>EISBN: 9781467301978</identifier><identifier>EISBN: 1467301973</identifier><identifier>EISBN: 146730199X</identifier><identifier>DOI: 10.1109/ICSAI.2012.6223216</identifier><language>eng</language><publisher>IEEE</publisher><subject>3D reconstruction ; Biological tissues ; BP neural network ; Cameras ; Computational modeling ; Image reconstruction ; Materials ; miniature pressure sensor ; parameter measurement ; Solid modeling ; Three dimensional displays</subject><ispartof>2012 International Conference on Systems and Informatics (ICSAI2012), 2012, p.1057-1060</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6223216$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2056,27924,54919</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6223216$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Xiangyun Liao</creatorcontrib><creatorcontrib>Weixin Si</creatorcontrib><creatorcontrib>Zhaoliang Duan</creatorcontrib><creatorcontrib>Xi Chen</creatorcontrib><creatorcontrib>Jianhui Zhao</creatorcontrib><creatorcontrib>Zhiyong Yuan</creatorcontrib><title>Parameter measurement of 3D soft tissue model in warping simulation</title><title>2012 International Conference on Systems and Informatics (ICSAI2012)</title><addtitle>ICSAI</addtitle><description>Parameter measurement of 3D soft tissue model is of great theoretical significance and application value in virtual surgery training simulation system. To solve the problems of existing soft tissue parameter measurement methods with high complexity, we propose a fast and effective parameter measurement method. We adopt a pillow as test material and exert pressure on it to simulate the parameter measurement of 3D soft tissue model in warping simulation. During the experiment, we construct a motion capture system with 3 cameras to obtain the warping set of the soft tissue model and carry out the 3D reconstruction of it by utilizing reverse engineering method. We obtain the pressure by using a miniature pressure sensor and calibrate the pressure sensor with BP (Back Propagation) neural network and then we calculate the 3D soft tissue parameter by using the pressure data and the 3D reconstruction result. The experimental results show that the parameter measurement method we proposed can obtain the parameter of 3D soft tissue model fast and effectively.</description><subject>3D reconstruction</subject><subject>Biological tissues</subject><subject>BP neural network</subject><subject>Cameras</subject><subject>Computational modeling</subject><subject>Image reconstruction</subject><subject>Materials</subject><subject>miniature pressure sensor</subject><subject>parameter measurement</subject><subject>Solid modeling</subject><subject>Three dimensional displays</subject><isbn>9781467301985</isbn><isbn>1467301981</isbn><isbn>9781467301992</isbn><isbn>9781467301978</isbn><isbn>1467301973</isbn><isbn>146730199X</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVj8tKxDAYRiMiKGNfQDd5gdZc_tyWQ70VBhSc_ZCZ_pFI0w5Ji_j2Cs5mvs3hbA58hNxx1nDO3EPXfqy7RjAuGi2EFFxfkMoZy0Ebybhz4vLMrbomVSlf7G_GWAC4Ie27zz7hjJkm9GXJmHCc6RSofKRlCjOdYykL0jT1ONA40m-fj3H8pCWmZfBznMZbchX8ULA6cUW2z0_b9rXevL107XpTR8fm2gRnDwG5M9qj2e-NQwcIgUulgwWjem6UNgygBy2Dlc4G1-seLBykUlquyP1_NiLi7phj8vlnd3oufwFoMEuH</recordid><startdate>201205</startdate><enddate>201205</enddate><creator>Xiangyun Liao</creator><creator>Weixin Si</creator><creator>Zhaoliang Duan</creator><creator>Xi Chen</creator><creator>Jianhui Zhao</creator><creator>Zhiyong Yuan</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201205</creationdate><title>Parameter measurement of 3D soft tissue model in warping simulation</title><author>Xiangyun Liao ; Weixin Si ; Zhaoliang Duan ; Xi Chen ; Jianhui Zhao ; Zhiyong Yuan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-7f98cfe1976ae7bb79e94e4f1356f8475d17567044d463f8398f9d6d484c35563</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>3D reconstruction</topic><topic>Biological tissues</topic><topic>BP neural network</topic><topic>Cameras</topic><topic>Computational modeling</topic><topic>Image reconstruction</topic><topic>Materials</topic><topic>miniature pressure sensor</topic><topic>parameter measurement</topic><topic>Solid modeling</topic><topic>Three dimensional displays</topic><toplevel>online_resources</toplevel><creatorcontrib>Xiangyun Liao</creatorcontrib><creatorcontrib>Weixin Si</creatorcontrib><creatorcontrib>Zhaoliang Duan</creatorcontrib><creatorcontrib>Xi Chen</creatorcontrib><creatorcontrib>Jianhui Zhao</creatorcontrib><creatorcontrib>Zhiyong Yuan</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Xiangyun Liao</au><au>Weixin Si</au><au>Zhaoliang Duan</au><au>Xi Chen</au><au>Jianhui Zhao</au><au>Zhiyong Yuan</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Parameter measurement of 3D soft tissue model in warping simulation</atitle><btitle>2012 International Conference on Systems and Informatics (ICSAI2012)</btitle><stitle>ICSAI</stitle><date>2012-05</date><risdate>2012</risdate><spage>1057</spage><epage>1060</epage><pages>1057-1060</pages><isbn>9781467301985</isbn><isbn>1467301981</isbn><eisbn>9781467301992</eisbn><eisbn>9781467301978</eisbn><eisbn>1467301973</eisbn><eisbn>146730199X</eisbn><abstract>Parameter measurement of 3D soft tissue model is of great theoretical significance and application value in virtual surgery training simulation system. To solve the problems of existing soft tissue parameter measurement methods with high complexity, we propose a fast and effective parameter measurement method. We adopt a pillow as test material and exert pressure on it to simulate the parameter measurement of 3D soft tissue model in warping simulation. During the experiment, we construct a motion capture system with 3 cameras to obtain the warping set of the soft tissue model and carry out the 3D reconstruction of it by utilizing reverse engineering method. We obtain the pressure by using a miniature pressure sensor and calibrate the pressure sensor with BP (Back Propagation) neural network and then we calculate the 3D soft tissue parameter by using the pressure data and the 3D reconstruction result. The experimental results show that the parameter measurement method we proposed can obtain the parameter of 3D soft tissue model fast and effectively.</abstract><pub>IEEE</pub><doi>10.1109/ICSAI.2012.6223216</doi><tpages>4</tpages></addata></record> |
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| identifier | ISBN: 9781467301985 |
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| language | eng |
| recordid | cdi_ieee_primary_6223216 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | 3D reconstruction Biological tissues BP neural network Cameras Computational modeling Image reconstruction Materials miniature pressure sensor parameter measurement Solid modeling Three dimensional displays |
| title | Parameter measurement of 3D soft tissue model in warping simulation |
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