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| Main Authors: | , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.08490 |
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| _version_ | 1866917073690558464 |
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| author | Smith, Mariana Watts, Tanner Stern, Susheela Sharma Burkhart, Brendan Li, Hao Chara, Alejandro O. Kumar, Nithesh Ferguson, James Acar, Ayberk d'Almeida, Jesse F. Branscombe, Lauren Shepard, Lauren Ghazi, Ahmed Oguz, Ipek Wu, Jie Ying Webster III, Robert J. Krieger, Axel Kuntz, Alan |
| author_facet | Smith, Mariana Watts, Tanner Stern, Susheela Sharma Burkhart, Brendan Li, Hao Chara, Alejandro O. Kumar, Nithesh Ferguson, James Acar, Ayberk d'Almeida, Jesse F. Branscombe, Lauren Shepard, Lauren Ghazi, Ahmed Oguz, Ipek Wu, Jie Ying Webster III, Robert J. Krieger, Axel Kuntz, Alan |
| contents | Concentric tube robots (CTRs) offer dexterous motion at millimeter scales, enabling minimally invasive procedures through natural orifices. This work presents a coordinated model-based resection planner and learning-based retraction network that work together to enable semi-autonomous tissue resection using a dual-arm transurethral concentric tube robot (the Virtuoso). The resection planner operates directly on segmented CT volumes of prostate phantoms, automatically generating tool trajectories for a three-phase median lobe resection workflow: left/median trough resection, right/median trough resection, and median blunt dissection. The retraction network, PushCVAE, trained on surgeon demonstrations, generates retractions according to the procedural phase. The procedure is executed under Level-3 (supervised) autonomy on a prostate phantom composed of hydrogel materials that replicate the mechanical and cutting properties of tissue. As a feasibility study, we demonstrate that our combined autonomous system achieves a 97.1% resection of the targeted volume of the median lobe. Our study establishes a foundation for image-guided autonomy in transurethral robotic surgery and represents a first step toward fully automated minimally-invasive prostate enucleation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_08490 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Supervised Autonomous Resection and Retraction Framework for Transurethral Enucleation of the Prostatic Median Lobe Smith, Mariana Watts, Tanner Stern, Susheela Sharma Burkhart, Brendan Li, Hao Chara, Alejandro O. Kumar, Nithesh Ferguson, James Acar, Ayberk d'Almeida, Jesse F. Branscombe, Lauren Shepard, Lauren Ghazi, Ahmed Oguz, Ipek Wu, Jie Ying Webster III, Robert J. Krieger, Axel Kuntz, Alan Robotics Concentric tube robots (CTRs) offer dexterous motion at millimeter scales, enabling minimally invasive procedures through natural orifices. This work presents a coordinated model-based resection planner and learning-based retraction network that work together to enable semi-autonomous tissue resection using a dual-arm transurethral concentric tube robot (the Virtuoso). The resection planner operates directly on segmented CT volumes of prostate phantoms, automatically generating tool trajectories for a three-phase median lobe resection workflow: left/median trough resection, right/median trough resection, and median blunt dissection. The retraction network, PushCVAE, trained on surgeon demonstrations, generates retractions according to the procedural phase. The procedure is executed under Level-3 (supervised) autonomy on a prostate phantom composed of hydrogel materials that replicate the mechanical and cutting properties of tissue. As a feasibility study, we demonstrate that our combined autonomous system achieves a 97.1% resection of the targeted volume of the median lobe. Our study establishes a foundation for image-guided autonomy in transurethral robotic surgery and represents a first step toward fully automated minimally-invasive prostate enucleation. |
| title | A Supervised Autonomous Resection and Retraction Framework for Transurethral Enucleation of the Prostatic Median Lobe |
| topic | Robotics |
| url | https://arxiv.org/abs/2511.08490 |