待翻譯：MISTac: A Vision-Based Tactile Sensor for Minimally Invasive Surgery
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.14772v1 Announce Type: new Abstract: Minimally invasive and robot-assisted surgery offer many advantages over traditional open surgery, but deprive surgeons of tactile feedback and the ability to palpate tissue with their fingers. To address this lack of tactile feedback, we introduce the MISTac, a high resolution vision-based tactile sensor specifically designed for palpation in MIS. The sensor has a replaceable sensor tip with a diameter of 8 mm which allows it to fit through the trocars used in minimally invasive surgery. Its modular 3D-printed case design allows the use of bulky off-the-shelf illumination and imaging hardware that can easily be exchanged and upgraded. The sensor has an optical resolution of 176.68 $\mu m$, a tactile resolution of 250 $\mu m$, and can resolve forces as little as 24.3 mN. An in vivo study with the sensor shows its usability in minimally invasive surgery. We trained a machine learning model with the tactile data collected in the trial on a tissue classification task achieving an aggregate accuracy of ~84% in a leave-one-out cross validation. Tactile sensors have the potential to one day aid surgeons during minimally invasive surgery with tasks such as tissue classification or intra-operative tumor localization; MISTac is a small step towards this vision. We open-source MISTac at https://github.com/lasr-lab/mistac
AI 服務暫時不可用，以下為來源正文，待恢復後補全翻譯。
--> [Submitted on 14 Aug 2026] Title:MISTac: A Vision-Based Tactile Sensor for Minimally Invasive Surgery View a PDF of the paper titled MISTac: A Vision-Based Tactile Sensor for Minimally Invasive Surgery, by Robin Koch and 7 other authors View PDF HTML (experimental) Abstract:Minimally invasive and robot-assisted surgery offer many advantages over traditional open surgery, but deprive surgeons of tactile feedback and the ability to palpate tissue with their fingers. To address this lack of tactile feedback, we introduce the MISTac, a high resolution vision-based tactile sensor specifically designed for palpation in MIS. The sensor has a replaceable sensor tip with a diameter of 8 mm which allows it to fit through the trocars used in minimally invasive surgery. Its modular 3D-printed case design allows the use of bulky off-the-shelf illumination and imaging hardware that can easily be exchanged and upgraded. The sensor has an optical resolution of 176.68 $\mu m$, a tactile resolution of 250 $\mu m$, and can resolve forces as little as 24.3 mN. An in vivo study with the sensor shows its usability in minimally invasive surgery. We trained a machine learning model with the tactile data collected in the trial on a tissue classification task achieving an aggregate accuracy of ~84% in a leave-one-out cross validation. Tactile sensors have the potential to one day aid surgeons during minimally invasive surgery with tasks such as tissue classification or intra-operative tumor localization; MISTac is a small step towards this vision. We open-source MISTac at this https URL Comments: This work has been submitted to the IEEE for possible publication Subjects: Robotics (cs.RO) Cite as: arXiv:2608.14772 [cs.RO] (or arXiv:2608.14772v1 [cs.RO] for this version) https://doi.org/10.48550/arXiv.2608.14772 arXiv-issued DOI via DataCite (pending registration) Submission history From: Robin Koch [view email] [v1] Fri, 14 Aug 2026 15:52:06 UTC (42,220 KB) Full-text links: Access Paper: View a PDF of the paper titled MISTac: A Vision-Based Tactile Sensor for Minimally Invasive Surgery, by Robin Koch and 7 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.RO new | recent | 2026-08 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Loading... Data provided by: Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)