Autonomous Tissue Retraction in Robotic Assisted Minimally Invasive Surgery – A Feasibility Study
暂无分享,去创建一个
Alejandro F. Frangi | Pietro Valdastri | Matteo Leonetti | Alejandro F Frangi | Aleks Attanasio | Bruno Scaglioni | William Cross | Chandra Shekhar Biyani | P. Valdastri | M. Leonetti | C. Biyani | Bruno Scaglioni | W. Cross | Aleks Attanasio
[1] Chi-Wing Fu,et al. H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation From CT Volumes , 2018, IEEE Transactions on Medical Imaging.
[2] Peter Kazanzides,et al. An open-source research kit for the da Vinci® Surgical System , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[3] Danail Stoyanov,et al. Implicit domain adaptation with conditional generative adversarial networks for depth prediction in endoscopy , 2019, International Journal of Computer Assisted Radiology and Surgery.
[4] Elena De Momi,et al. Automated Pick-Up of Suturing Needles for Robotic Surgical Assistance , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[5] Ron Alterovitz,et al. Toward automated tissue retraction in robot-assisted surgery , 2010, 2010 IEEE International Conference on Robotics and Automation.
[6] Richard I. Hartley,et al. Theory and Practice of Projective Rectification , 1999, International Journal of Computer Vision.
[7] Klaus H. Maier-Hein,et al. Brain Tumor Segmentation Using Large Receptive Field Deep Convolutional Neural Networks , 2017, Bildverarbeitung für die Medizin.
[8] Riccardo Muradore,et al. Development of a Cognitive Robotic System for Simple Surgical Tasks , 2015 .
[9] Imre J. Rudas,et al. Ontology-Based Surgical Subtask Automation, Automating Blunt Dissection , 2018, J. Medical Robotics Res..
[10] F. Anderhuber,et al. Flexibility of Thiel’s embalmed cadavers: the explanation is probably in the muscles , 2011, Surgical and Radiologic Anatomy.
[11] Danail Stoyanov,et al. EasyLabels: weak labels for scene segmentation in laparoscopic videos , 2019, International Journal of Computer Assisted Radiology and Surgery.
[12] Heiko Hirschmüller,et al. Stereo Processing by Semiglobal Matching and Mutual Information , 2008, IEEE Trans. Pattern Anal. Mach. Intell..
[13] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[14] Ryan K. Orosco,et al. SuPer: A Surgical Perception Framework for Endoscopic Tissue Manipulation With Surgical Robotics , 2020, IEEE Robotics and Automation Letters.
[15] Axel Krieger,et al. Development and Feasibility of a Robotic Laparoscopic Clipping Tool for Wound Closure and Anastomosis. , 2018, Journal of medical devices.
[16] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[17] Imre J. Rudas,et al. Towards surgical subtask automation — Blunt dissection , 2017, 2017 IEEE 21st International Conference on Intelligent Engineering Systems (INES).
[18] Holger Roth,et al. Unsupervised segmentation of 3D medical images based on clustering and deep representation learning , 2018, Medical Imaging.
[19] May Liu,et al. A Review of Training Research and Virtual Reality Simulators for the da Vinci Surgical System , 2015, Teaching and learning in medicine.
[20] Pieter Abbeel,et al. Learning by observation for surgical subtasks: Multilateral cutting of 3D viscoelastic and 2D Orthotropic Tissue Phantoms , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).
[21] Zhengyou Zhang,et al. A Flexible New Technique for Camera Calibration , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[22] Pieter Abbeel,et al. Autonomous multilateral debridement with the Raven surgical robot , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[23] Imre J. Rudas,et al. Surgical subtask automation — Soft tissue retraction , 2018, 2018 IEEE 16th World Symposium on Applied Machine Intelligence and Informatics (SAMI).
[24] Seyed-Ahmad Ahmadi,et al. V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation , 2016, 2016 Fourth International Conference on 3D Vision (3DV).
[25] J. Anger,et al. Safety, efficiency and learning curves in robotic surgery: a human factors analysis , 2016, Surgical Endoscopy.
[26] P R C Steele,et al. Current and future practices in surgical retraction. , 2013, The surgeon : journal of the Royal Colleges of Surgeons of Edinburgh and Ireland.
[27] Jim C Hu,et al. Perioperative complications of laparoscopic and robotic assisted laparoscopic radical prostatectomy. , 2006, The Journal of urology.
[28] Milan Sonka,et al. 3D Slicer as an image computing platform for the Quantitative Imaging Network. , 2012, Magnetic resonance imaging.
[29] M. Stone. Cross‐Validatory Choice and Assessment of Statistical Predictions , 1976 .
[30] Giancarlo Ferrigno,et al. “Deep-Onto” network for surgical workflow and context recognition , 2018, International Journal of Computer Assisted Radiology and Surgery.
[31] Henry C. Lin,et al. JHU-ISI Gesture and Skill Assessment Working Set ( JIGSAWS ) : A Surgical Activity Dataset for Human Motion Modeling , 2014 .
[32] Kenneth Y. Goldberg,et al. Automating multi-throw multilateral surgical suturing with a mechanical needle guide and sequential convex optimization , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).
[33] Brian S. Peters,et al. Review of emerging surgical robotic technology , 2018, Surgical Endoscopy.
[34] J. Carmichael,et al. Comparison of open, laparoscopic, and robotic approaches for total abdominal colectomy , 2016, Surgical Endoscopy.
[35] Manbae Kim,et al. 2D to 3D stereoscopic conversion: depth-map estimation in a 2D single-view image , 2007, SPIE Optical Engineering + Applications.
[36] Kenneth Y. Goldberg,et al. An interchangeable surgical instrument system with application to supervised automation of multilateral tumor resection , 2016, 2016 IEEE International Conference on Automation Science and Engineering (CASE).
[37] Eero P. Simoncelli,et al. Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.