Loading…
Neurosurgical robotic arm drilling navigation system
Background The aim of this work was to develop a neurosurgical robotic arm drilling navigation system that provides assistance throughout the complete bone drilling process. Methods The system comprised neurosurgical robotic arm navigation combining robotic and surgical navigation, 3D medical imagin...
Saved in:
| Published in: | The international journal of medical robotics + computer assisted surgery 2017-09, Vol.13 (3), p.n/a |
|---|---|
| Main Authors: | , , , , |
| Format: | Article |
| Language: | English |
| Subjects: | |
| Citations: | Items that this one cites Items that cite this one |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| cited_by | cdi_FETCH-LOGICAL-c3970-9624ddb7776f95a14a1dc8b7c302277d48b972cbbf984b850c4132f555c27aac3 |
|---|---|
| cites | cdi_FETCH-LOGICAL-c3970-9624ddb7776f95a14a1dc8b7c302277d48b972cbbf984b850c4132f555c27aac3 |
| container_end_page | n/a |
| container_issue | 3 |
| container_start_page | |
| container_title | The international journal of medical robotics + computer assisted surgery |
| container_volume | 13 |
| creator | Lin, Chung‐Chih Lin, Hsin‐Cheng Lee, Wen‐Yo Lee, Shih‐Tseng Wu, Chieh‐Tsai |
| description | Background
The aim of this work was to develop a neurosurgical robotic arm drilling navigation system that provides assistance throughout the complete bone drilling process.
Methods
The system comprised neurosurgical robotic arm navigation combining robotic and surgical navigation, 3D medical imaging based surgical planning that could identify lesion location and plan the surgical path on 3D images, and automatic bone drilling control that would stop drilling when the bone was to be drilled‐through. Three kinds of experiment were designed.
Results
The average positioning error deduced from 3D images of the robotic arm was 0.502 ± 0.069 mm. The correlation between automatically and manually planned paths was 0.975. The average distance error between automatically planned paths and risky zones was 0.279 ± 0.401 mm. The drilling auto‐stopping algorithm had 0.00% unstopped cases (26.32% in control group 1) and 70.53% non‐drilled‐through cases (8.42% and 4.21% in control groups 1 and 2).
Conclusions
The system may be useful for neurosurgical robotic arm drilling navigation. |
| doi_str_mv | 10.1002/rcs.1790 |
| format | article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1845816884</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1940328172</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3970-9624ddb7776f95a14a1dc8b7c302277d48b972cbbf984b850c4132f555c27aac3</originalsourceid><addsrcrecordid>eNp1kF1LwzAUQIMobk7BXyAFX3zpTNKkSR5l-AVDwQ_wLSRpOjLSdiat0n9v5-YEwad7Hw6Hew8ApwhOEYT4Mpg4RUzAPTBGhPGUivxtf7dTNAJHMS4hJJTk5BCMMBMIYkjHgDzYLjSxCwtnlE9Co5vWmUSFKimC897Vi6RWH26hWtfUSexja6tjcFAqH-3Jdk7A6831y-wunT_e3s-u5qnJBIOpyDEpCs0Yy0tBFSIKFYZrZjKIMWMF4VowbLQuBSeaU2gIynBJKTWYKWWyCbjYeFehee9sbGXlorHeq9o2XZSIE8pRzjkZ0PM_6LLpQj1cJ5EgMMMcMfwrNMPPMdhSroKrVOglgnJdUg4l5brkgJ5thZ2ubLEDf9INQLoBPp23_b8i-TR7_hZ-AR9yezw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1940328172</pqid></control><display><type>article</type><title>Neurosurgical robotic arm drilling navigation system</title><source>Wiley-Blackwell Read & Publish Collection</source><creator>Lin, Chung‐Chih ; Lin, Hsin‐Cheng ; Lee, Wen‐Yo ; Lee, Shih‐Tseng ; Wu, Chieh‐Tsai</creator><creatorcontrib>Lin, Chung‐Chih ; Lin, Hsin‐Cheng ; Lee, Wen‐Yo ; Lee, Shih‐Tseng ; Wu, Chieh‐Tsai</creatorcontrib><description>Background
The aim of this work was to develop a neurosurgical robotic arm drilling navigation system that provides assistance throughout the complete bone drilling process.
Methods
The system comprised neurosurgical robotic arm navigation combining robotic and surgical navigation, 3D medical imaging based surgical planning that could identify lesion location and plan the surgical path on 3D images, and automatic bone drilling control that would stop drilling when the bone was to be drilled‐through. Three kinds of experiment were designed.
Results
The average positioning error deduced from 3D images of the robotic arm was 0.502 ± 0.069 mm. The correlation between automatically and manually planned paths was 0.975. The average distance error between automatically planned paths and risky zones was 0.279 ± 0.401 mm. The drilling auto‐stopping algorithm had 0.00% unstopped cases (26.32% in control group 1) and 70.53% non‐drilled‐through cases (8.42% and 4.21% in control groups 1 and 2).
Conclusions
The system may be useful for neurosurgical robotic arm drilling navigation.</description><identifier>ISSN: 1478-5951</identifier><identifier>EISSN: 1478-596X</identifier><identifier>DOI: 10.1002/rcs.1790</identifier><identifier>PMID: 27910205</identifier><language>eng</language><publisher>England: Wiley Subscription Services, Inc</publisher><subject>3d printing ; Algorithms ; Animals ; Automatic control ; Biomechanical Phenomena ; Bone and Bones - surgery ; bone drilling ; Drilling ; Equipment Design ; haptic device ; Humans ; Imaging, Three-Dimensional - statistics & numerical data ; Medical imaging ; Models, Anatomic ; Models, Animal ; Navigation systems ; Neurosurgical Procedures - instrumentation ; Neurosurgical Procedures - statistics & numerical data ; neurosurgical robot ; Phantoms, Imaging ; Robot arms ; robotic arm ; Robotic Surgical Procedures - instrumentation ; Robotic Surgical Procedures - statistics & numerical data ; Robotics ; Skull - surgery ; Surgery, Computer-Assisted - instrumentation ; Surgery, Computer-Assisted - statistics & numerical data ; Sus scrofa ; Three dimensional imaging</subject><ispartof>The international journal of medical robotics + computer assisted surgery, 2017-09, Vol.13 (3), p.n/a</ispartof><rights>Copyright © 2016 John Wiley & Sons, Ltd.</rights><rights>Copyright © 2017 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3970-9624ddb7776f95a14a1dc8b7c302277d48b972cbbf984b850c4132f555c27aac3</citedby><cites>FETCH-LOGICAL-c3970-9624ddb7776f95a14a1dc8b7c302277d48b972cbbf984b850c4132f555c27aac3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27910205$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lin, Chung‐Chih</creatorcontrib><creatorcontrib>Lin, Hsin‐Cheng</creatorcontrib><creatorcontrib>Lee, Wen‐Yo</creatorcontrib><creatorcontrib>Lee, Shih‐Tseng</creatorcontrib><creatorcontrib>Wu, Chieh‐Tsai</creatorcontrib><title>Neurosurgical robotic arm drilling navigation system</title><title>The international journal of medical robotics + computer assisted surgery</title><addtitle>Int J Med Robot</addtitle><description>Background
The aim of this work was to develop a neurosurgical robotic arm drilling navigation system that provides assistance throughout the complete bone drilling process.
Methods
The system comprised neurosurgical robotic arm navigation combining robotic and surgical navigation, 3D medical imaging based surgical planning that could identify lesion location and plan the surgical path on 3D images, and automatic bone drilling control that would stop drilling when the bone was to be drilled‐through. Three kinds of experiment were designed.
Results
The average positioning error deduced from 3D images of the robotic arm was 0.502 ± 0.069 mm. The correlation between automatically and manually planned paths was 0.975. The average distance error between automatically planned paths and risky zones was 0.279 ± 0.401 mm. The drilling auto‐stopping algorithm had 0.00% unstopped cases (26.32% in control group 1) and 70.53% non‐drilled‐through cases (8.42% and 4.21% in control groups 1 and 2).
Conclusions
The system may be useful for neurosurgical robotic arm drilling navigation.</description><subject>3d printing</subject><subject>Algorithms</subject><subject>Animals</subject><subject>Automatic control</subject><subject>Biomechanical Phenomena</subject><subject>Bone and Bones - surgery</subject><subject>bone drilling</subject><subject>Drilling</subject><subject>Equipment Design</subject><subject>haptic device</subject><subject>Humans</subject><subject>Imaging, Three-Dimensional - statistics & numerical data</subject><subject>Medical imaging</subject><subject>Models, Anatomic</subject><subject>Models, Animal</subject><subject>Navigation systems</subject><subject>Neurosurgical Procedures - instrumentation</subject><subject>Neurosurgical Procedures - statistics & numerical data</subject><subject>neurosurgical robot</subject><subject>Phantoms, Imaging</subject><subject>Robot arms</subject><subject>robotic arm</subject><subject>Robotic Surgical Procedures - instrumentation</subject><subject>Robotic Surgical Procedures - statistics & numerical data</subject><subject>Robotics</subject><subject>Skull - surgery</subject><subject>Surgery, Computer-Assisted - instrumentation</subject><subject>Surgery, Computer-Assisted - statistics & numerical data</subject><subject>Sus scrofa</subject><subject>Three dimensional imaging</subject><issn>1478-5951</issn><issn>1478-596X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp1kF1LwzAUQIMobk7BXyAFX3zpTNKkSR5l-AVDwQ_wLSRpOjLSdiat0n9v5-YEwad7Hw6Hew8ApwhOEYT4Mpg4RUzAPTBGhPGUivxtf7dTNAJHMS4hJJTk5BCMMBMIYkjHgDzYLjSxCwtnlE9Co5vWmUSFKimC897Vi6RWH26hWtfUSexja6tjcFAqH-3Jdk7A6831y-wunT_e3s-u5qnJBIOpyDEpCs0Yy0tBFSIKFYZrZjKIMWMF4VowbLQuBSeaU2gIynBJKTWYKWWyCbjYeFehee9sbGXlorHeq9o2XZSIE8pRzjkZ0PM_6LLpQj1cJ5EgMMMcMfwrNMPPMdhSroKrVOglgnJdUg4l5brkgJ5thZ2ubLEDf9INQLoBPp23_b8i-TR7_hZ-AR9yezw</recordid><startdate>201709</startdate><enddate>201709</enddate><creator>Lin, Chung‐Chih</creator><creator>Lin, Hsin‐Cheng</creator><creator>Lee, Wen‐Yo</creator><creator>Lee, Shih‐Tseng</creator><creator>Wu, Chieh‐Tsai</creator><general>Wiley Subscription Services, Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>JQ2</scope><scope>K9.</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7X8</scope></search><sort><creationdate>201709</creationdate><title>Neurosurgical robotic arm drilling navigation system</title><author>Lin, Chung‐Chih ; Lin, Hsin‐Cheng ; Lee, Wen‐Yo ; Lee, Shih‐Tseng ; Wu, Chieh‐Tsai</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3970-9624ddb7776f95a14a1dc8b7c302277d48b972cbbf984b850c4132f555c27aac3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>3d printing</topic><topic>Algorithms</topic><topic>Animals</topic><topic>Automatic control</topic><topic>Biomechanical Phenomena</topic><topic>Bone and Bones - surgery</topic><topic>bone drilling</topic><topic>Drilling</topic><topic>Equipment Design</topic><topic>haptic device</topic><topic>Humans</topic><topic>Imaging, Three-Dimensional - statistics & numerical data</topic><topic>Medical imaging</topic><topic>Models, Anatomic</topic><topic>Models, Animal</topic><topic>Navigation systems</topic><topic>Neurosurgical Procedures - instrumentation</topic><topic>Neurosurgical Procedures - statistics & numerical data</topic><topic>neurosurgical robot</topic><topic>Phantoms, Imaging</topic><topic>Robot arms</topic><topic>robotic arm</topic><topic>Robotic Surgical Procedures - instrumentation</topic><topic>Robotic Surgical Procedures - statistics & numerical data</topic><topic>Robotics</topic><topic>Skull - surgery</topic><topic>Surgery, Computer-Assisted - instrumentation</topic><topic>Surgery, Computer-Assisted - statistics & numerical data</topic><topic>Sus scrofa</topic><topic>Three dimensional imaging</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lin, Chung‐Chih</creatorcontrib><creatorcontrib>Lin, Hsin‐Cheng</creatorcontrib><creatorcontrib>Lee, Wen‐Yo</creatorcontrib><creatorcontrib>Lee, Shih‐Tseng</creatorcontrib><creatorcontrib>Wu, Chieh‐Tsai</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>MEDLINE - Academic</collection><jtitle>The international journal of medical robotics + computer assisted surgery</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lin, Chung‐Chih</au><au>Lin, Hsin‐Cheng</au><au>Lee, Wen‐Yo</au><au>Lee, Shih‐Tseng</au><au>Wu, Chieh‐Tsai</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Neurosurgical robotic arm drilling navigation system</atitle><jtitle>The international journal of medical robotics + computer assisted surgery</jtitle><addtitle>Int J Med Robot</addtitle><date>2017-09</date><risdate>2017</risdate><volume>13</volume><issue>3</issue><epage>n/a</epage><issn>1478-5951</issn><eissn>1478-596X</eissn><abstract>Background
The aim of this work was to develop a neurosurgical robotic arm drilling navigation system that provides assistance throughout the complete bone drilling process.
Methods
The system comprised neurosurgical robotic arm navigation combining robotic and surgical navigation, 3D medical imaging based surgical planning that could identify lesion location and plan the surgical path on 3D images, and automatic bone drilling control that would stop drilling when the bone was to be drilled‐through. Three kinds of experiment were designed.
Results
The average positioning error deduced from 3D images of the robotic arm was 0.502 ± 0.069 mm. The correlation between automatically and manually planned paths was 0.975. The average distance error between automatically planned paths and risky zones was 0.279 ± 0.401 mm. The drilling auto‐stopping algorithm had 0.00% unstopped cases (26.32% in control group 1) and 70.53% non‐drilled‐through cases (8.42% and 4.21% in control groups 1 and 2).
Conclusions
The system may be useful for neurosurgical robotic arm drilling navigation.</abstract><cop>England</cop><pub>Wiley Subscription Services, Inc</pub><pmid>27910205</pmid><doi>10.1002/rcs.1790</doi><tpages>9</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1478-5951 |
| ispartof | The international journal of medical robotics + computer assisted surgery, 2017-09, Vol.13 (3), p.n/a |
| issn | 1478-5951 1478-596X |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1845816884 |
| source | Wiley-Blackwell Read & Publish Collection |
| subjects | 3d printing Algorithms Animals Automatic control Biomechanical Phenomena Bone and Bones - surgery bone drilling Drilling Equipment Design haptic device Humans Imaging, Three-Dimensional - statistics & numerical data Medical imaging Models, Anatomic Models, Animal Navigation systems Neurosurgical Procedures - instrumentation Neurosurgical Procedures - statistics & numerical data neurosurgical robot Phantoms, Imaging Robot arms robotic arm Robotic Surgical Procedures - instrumentation Robotic Surgical Procedures - statistics & numerical data Robotics Skull - surgery Surgery, Computer-Assisted - instrumentation Surgery, Computer-Assisted - statistics & numerical data Sus scrofa Three dimensional imaging |
| title | Neurosurgical robotic arm drilling navigation system |
| url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T22%3A49%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Neurosurgical%20robotic%20arm%20drilling%20navigation%20system&rft.jtitle=The%20international%20journal%20of%20medical%20robotics%20+%20computer%20assisted%20surgery&rft.au=Lin,%20Chung%E2%80%90Chih&rft.date=2017-09&rft.volume=13&rft.issue=3&rft.epage=n/a&rft.issn=1478-5951&rft.eissn=1478-596X&rft_id=info:doi/10.1002/rcs.1790&rft_dat=%3Cproquest_cross%3E1940328172%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c3970-9624ddb7776f95a14a1dc8b7c302277d48b972cbbf984b850c4132f555c27aac3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1940328172&rft_id=info:pmid/27910205&rfr_iscdi=true |