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class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Robotics">cs.RO</span> </div> </div> <p class="title is-5 mathjax"> From Monocular Vision to Autonomous Action: Guiding Tumor Resection via 3D Reconstruction </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Acar%2C+A">Ayberk Acar</a>, <a href="/search/cs?searchtype=author&amp;query=Smith%2C+M">Mariana Smith</a>, <a href="/search/cs?searchtype=author&amp;query=Al-Zogbi%2C+L">Lidia Al-Zogbi</a>, <a href="/search/cs?searchtype=author&amp;query=Watts%2C+T">Tanner Watts</a>, <a href="/search/cs?searchtype=author&amp;query=Li%2C+F">Fangjie Li</a>, <a href="/search/cs?searchtype=author&amp;query=Li%2C+H">Hao Li</a>, <a href="/search/cs?searchtype=author&amp;query=Yilmaz%2C+N">Nural Yilmaz</a>, <a href="/search/cs?searchtype=author&amp;query=Scheikl%2C+P+M">Paul Maria Scheikl</a>, <a href="/search/cs?searchtype=author&amp;query=d%27Almeida%2C+J+F">Jesse F. d&#39;Almeida</a>, <a href="/search/cs?searchtype=author&amp;query=Sharma%2C+S">Susheela Sharma</a>, <a href="/search/cs?searchtype=author&amp;query=Branscombe%2C+L">Lauren Branscombe</a>, <a href="/search/cs?searchtype=author&amp;query=Ertop%2C+T+E">Tayfun Efe Ertop</a>, <a href="/search/cs?searchtype=author&amp;query=Webster%2C+R+J">Robert J. Webster III</a>, <a href="/search/cs?searchtype=author&amp;query=Oguz%2C+I">Ipek Oguz</a>, <a href="/search/cs?searchtype=author&amp;query=Kuntz%2C+A">Alan Kuntz</a>, <a href="/search/cs?searchtype=author&amp;query=Krieger%2C+A">Axel Krieger</a>, <a href="/search/cs?searchtype=author&amp;query=Wu%2C+J+Y">Jie Ying Wu</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2503.16263v1-abstract-short" style="display: inline;"> Surgical automation requires precise guidance and understanding of the scene. Current methods in the literature rely on bulky depth cameras to create maps of the anatomy, however this does not translate well to space-limited clinical applications. Monocular cameras are small and allow minimally invasive surgeries in tight spaces but additional processing is required to generate 3D scene understand&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2503.16263v1-abstract-full').style.display = 'inline'; document.getElementById('2503.16263v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2503.16263v1-abstract-full" style="display: none;"> Surgical automation requires precise guidance and understanding of the scene. Current methods in the literature rely on bulky depth cameras to create maps of the anatomy, however this does not translate well to space-limited clinical applications. Monocular cameras are small and allow minimally invasive surgeries in tight spaces but additional processing is required to generate 3D scene understanding. We propose a 3D mapping pipeline that uses only RGB images to create segmented point clouds of the target anatomy. To ensure the most precise reconstruction, we compare different structure from motion algorithms&#39; performance on mapping the central airway obstructions, and test the pipeline on a downstream task of tumor resection. In several metrics, including post-procedure tissue model evaluation, our pipeline performs comparably to RGB-D cameras and, in some cases, even surpasses their performance. These promising results demonstrate that automation guidance can be achieved in minimally invasive procedures with monocular cameras. This study is a step toward the complete autonomy of surgical robots. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2503.16263v1-abstract-full').style.display = 'none'; document.getElementById('2503.16263v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 20 March, 2025; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2025. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">7 Pages, 8 Figures, 1 Table. This work has been submitted IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) for possible publication</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2211.02597">arXiv:2211.02597</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2211.02597">pdf</a>, <a href="https://arxiv.org/format/2211.02597">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Robotics">cs.RO</span> </div> </div> <p class="title is-5 mathjax"> Autonomous Medical Needle Steering In Vivo </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Kuntz%2C+A">Alan Kuntz</a>, <a href="/search/cs?searchtype=author&amp;query=Emerson%2C+M">Maxwell Emerson</a>, <a href="/search/cs?searchtype=author&amp;query=Ertop%2C+T+E">Tayfun Efe Ertop</a>, <a href="/search/cs?searchtype=author&amp;query=Fried%2C+I">Inbar Fried</a>, <a href="/search/cs?searchtype=author&amp;query=Fu%2C+M">Mengyu Fu</a>, <a href="/search/cs?searchtype=author&amp;query=Hoelscher%2C+J">Janine Hoelscher</a>, <a href="/search/cs?searchtype=author&amp;query=Rox%2C+M">Margaret Rox</a>, <a href="/search/cs?searchtype=author&amp;query=Akulian%2C+J">Jason Akulian</a>, <a href="/search/cs?searchtype=author&amp;query=Gillaspie%2C+E+A">Erin A. Gillaspie</a>, <a href="/search/cs?searchtype=author&amp;query=Lee%2C+Y+Z">Yueh Z. Lee</a>, <a href="/search/cs?searchtype=author&amp;query=Maldonado%2C+F">Fabien Maldonado</a>, <a href="/search/cs?searchtype=author&amp;query=Webster%2C+R+J">Robert J. Webster III</a>, <a href="/search/cs?searchtype=author&amp;query=Alterovitz%2C+R">Ron Alterovitz</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2211.02597v1-abstract-short" style="display: inline;"> The use of needles to access sites within organs is fundamental to many interventional medical procedures both for diagnosis and treatment. Safe and accurate navigation of a needle through living tissue to an intra-tissue target is currently often challenging or infeasible due to the presence of anatomical obstacles in the tissue, high levels of uncertainty, and natural tissue motion (e.g., due to&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2211.02597v1-abstract-full').style.display = 'inline'; document.getElementById('2211.02597v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2211.02597v1-abstract-full" style="display: none;"> The use of needles to access sites within organs is fundamental to many interventional medical procedures both for diagnosis and treatment. Safe and accurate navigation of a needle through living tissue to an intra-tissue target is currently often challenging or infeasible due to the presence of anatomical obstacles in the tissue, high levels of uncertainty, and natural tissue motion (e.g., due to breathing). Medical robots capable of automating needle-based procedures in vivo have the potential to overcome these challenges and enable an enhanced level of patient care and safety. In this paper, we show the first medical robot that autonomously navigates a needle inside living tissue around anatomical obstacles to an intra-tissue target. Our system leverages an aiming device and a laser-patterned highly flexible steerable needle, a type of needle capable of maneuvering along curvilinear trajectories to avoid obstacles. The autonomous robot accounts for anatomical obstacles and uncertainty in living tissue/needle interaction with replanning and control and accounts for respiratory motion by defining safe insertion time windows during the breathing cycle. We apply the system to lung biopsy, which is critical in the diagnosis of lung cancer, the leading cause of cancer-related death in the United States. We demonstrate successful performance of our system in multiple in vivo porcine studies and also demonstrate that our approach leveraging autonomous needle steering outperforms a standard manual clinical technique for lung nodule access. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2211.02597v1-abstract-full').style.display = 'none'; document.getElementById('2211.02597v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 4 November, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">22 pages, 6 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2101.04856">arXiv:2101.04856</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2101.04856">pdf</a>, <a href="https://arxiv.org/format/2101.04856">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Robotics">cs.RO</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Systems and Control">eess.SY</span> </div> </div> <p class="title is-5 mathjax"> A Recurrent Neural Network Approach to Roll Estimation for Needle Steering </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Emerson%2C+M">Maxwell Emerson</a>, <a href="/search/cs?searchtype=author&amp;query=Ferguson%2C+J+M">James M. Ferguson</a>, <a href="/search/cs?searchtype=author&amp;query=Ertop%2C+T+E">Tayfun Efe Ertop</a>, <a href="/search/cs?searchtype=author&amp;query=Rox%2C+M">Margaret Rox</a>, <a href="/search/cs?searchtype=author&amp;query=Granna%2C+J">Josephine Granna</a>, <a href="/search/cs?searchtype=author&amp;query=Lester%2C+M">Michael Lester</a>, <a href="/search/cs?searchtype=author&amp;query=Maldonado%2C+F">Fabien Maldonado</a>, <a href="/search/cs?searchtype=author&amp;query=Gillaspie%2C+E+A">Erin A. Gillaspie</a>, <a href="/search/cs?searchtype=author&amp;query=Alterovitz%2C+R">Ron Alterovitz</a>, <a href="/search/cs?searchtype=author&amp;query=III.%2C+R+J+W">Robert J. Webster III.</a>, <a href="/search/cs?searchtype=author&amp;query=Kuntz%2C+A">Alan Kuntz</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2101.04856v1-abstract-short" style="display: inline;"> Steerable needles are a promising technology for delivering targeted therapies in the body in a minimally-invasive fashion, as they can curve around anatomical obstacles and hone in on anatomical targets. In order to accurately steer them, controllers must have full knowledge of the needle tip&#39;s orientation. However, current sensors either do not provide full orientation information or interfere w&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2101.04856v1-abstract-full').style.display = 'inline'; document.getElementById('2101.04856v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2101.04856v1-abstract-full" style="display: none;"> Steerable needles are a promising technology for delivering targeted therapies in the body in a minimally-invasive fashion, as they can curve around anatomical obstacles and hone in on anatomical targets. In order to accurately steer them, controllers must have full knowledge of the needle tip&#39;s orientation. However, current sensors either do not provide full orientation information or interfere with the needle&#39;s ability to deliver therapy. Further, torsional dynamics can vary and depend on many parameters making steerable needles difficult to accurately model, limiting the effectiveness of traditional observer methods. To overcome these limitations, we propose a model-free, learned-method that leverages LSTM neural networks to estimate the needle tip&#39;s orientation online. We validate our method by integrating it into a sliding-mode controller and steering the needle to targets in gelatin and ex vivo ovine brain tissue. We compare our method&#39;s performance against an Extended Kalman Filter, a model-based observer, achieving significantly lower targeting errors. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2101.04856v1-abstract-full').style.display = 'none'; document.getElementById('2101.04856v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 12 January, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2021. </p> </li> </ol> <div class="is-hidden-tablet"> <!-- feedback for mobile only --> <span class="help" style="display: inline-block;"><a href="https://github.com/arXiv/arxiv-search/releases">Search v0.5.6 released 2020-02-24</a>&nbsp;&nbsp;</span> </div> </div> </main> <footer> <div class="columns is-desktop" role="navigation" aria-label="Secondary"> <!-- MetaColumn 1 --> <div 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