Publications

@article{Ramesh2023,

title = {TRandAugment: temporal random augmentation strategy for surgical activity recognition from videos},

author = {Sanat Ramesh and Diego Dall'Alba and Cristians Gonzalez and Tong Yu and Pietro Mascagni and Didier Mutter and Jacques Marescaux and Paolo Fiorini and Nicolas Padoy},

url = {https://doi.org/10.1007/s11548-023-02864-8},

doi = {10.1007/s11548-023-02864-8},

year  = {2023},

date = {2023-03-01},

urldate = {2023-03-01},

journal = {International Journal of Computer Assisted Radiology and Surgery},

publisher = {Springer Science and Business Media LLC},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10086537,

title = {Weakly Supervised Temporal Convolutional Networks for Fine-grained Surgical Activity Recognition},

author = {Sanat Ramesh and Diego Dall’Alba and Cristians Gonzalez and Tong Yu and Pietro Mascagni and Didier Mutter and Jacques Marescaux and Paolo Fiorini and Nicolas Padoy},

url = {https://arxiv.org/pdf/2302.10834.pdf},

doi = {10.1109/TMI.2023.3262847},

year  = {2023},

date = {2023-01-01},

journal = {IEEE Transactions on Medical Imaging},

pages = {1-1},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pore2023autonomous,

title = {Autonomous Navigation for Robot-Assisted Intraluminal and Endovascular Procedures: A Systematic Review},

author = {Ameya Pore and Zhen Li and Diego Dall'Alba and Albert Hernansanz and Elena De Momi and Arianna Menciassi and Alicia Casals Gelpí and Jenny Dankelman and Paolo Fiorini and Emmanuel Vander Poorten},

url = {https://atlas-itn.eu/wp-content/uploads/2023/08/IEEE_TRO_arxiv.pdf},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {IEEE Transactions on Robotics},

publisher = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{corsi2023constrained,

title = {Constrained reinforcement learning and formal verification for safe colonoscopy navigation},

author = {Davide Corsi and Luca Marzari and Ameya Pore and Alessandro Farinelli and Alicia Casals and Paolo Fiorini and Diego Dall'Alba},

url = {https://arxiv.org/abs/2303.03207},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {arXiv preprint arXiv:2303.03207},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Bloemberg2022,

title = {Design and evaluation of an MRI-ready, self-propelled needle for prostate interventions},

author = {Jette Bloemberg and Fabian Trauzettel and Bram Coolen and Dimitra Dodou and Paul Breedveld},

url = {https://repository.tudelft.nl/islandora/object/uuid:df086bc3-8d99-425d-9c66-e67abadcc115/datastream/OBJ/download},

doi = {10.1371/journal.pone.0274063},

issn = {1932-6203},

year  = {2022},

date = {2022-01-01},

journal = {PLOS ONE},

volume = {17},

issue = {9},

pages = {e0274063},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ha2022,

title = {Contact Localization of Continuum and Flexible Robot Using Data-driven Approach},

author = {Xuan Thao Ha and Di Wu and Chun-Feng Lai and Mouloud Ourak and Gianni Borghesan and Arianna Menciassi and Emmanuel Vander Poorten},

url = {https://atlas-itn.eu/wp-content/uploads/2022/06/Contact_Localization_XuanThaoHa.pdf},

year  = {2022},

date = {2022-01-01},

journal = {IEEE Robotics and Automation Letters},

publisher = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Wu2022,

title = {Deep-Learning-Based Compliant Motion Control of a Pneumatically-Driven Robotic Catheter},

author = {Di Wu and Xuan Thao Ha and Yao Zhang and Mouloud Ourak and Gianni Borghesan and Kenan Niu and Fabian Trauzettel and Jenny Dankelman and Arianna Menciassi and Emmanuel Vander Poorten},

url = {https://atlas-itn.eu/wp-content/uploads/2022/10/RAL_IROS2022_compliant_motion_control_rebuttal_final_submission-1.pdf},

year  = {2022},

date = {2022-01-01},

journal = {IEEE Robotics and Automation Letters},

volume = {7},

number = {4},

pages = {8853--8860},

publisher = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Sahu2022,

title = {A Spring-based Inductive Sensor for Soft and Flexible Robots},

author = {Sujit Kumar Sahu and Izadyar Tamadon and Benoit Rosa and Pierre Renaud and Arianna Menciassi},

doi = {10.1109/JSEN.2022.3201049},

year  = {2022},

date = {2022-01-01},

journal = {IEEE Sensors Journal},

pages = {1-1},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{liao2022distortion,

title = {Distortion and Instability Compensation with Deep Learning for Rotational Scanning Endoscopic Optical Coherence Tomography},

author = {Guiqiu Liao and Oscar Caravaca-Mora and Benoit Rosa and Philippe Zanne and Diego Dall Alba and Paolo Fiorini and Michel Mathelin and Florent Nageotte and Michalina J Gora},

doi = {https://doi.org/10.1016/j.media.2022.102355},

year  = {2022},

date = {2022-01-01},

journal = {Medical Image Analysis},

pages = {102355},

publisher = {Elsevier},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Pane2021,

title = {Dynamic tracking of a magnetic micro-roller using ultrasound phase analysis},

author = {Stefano Pane and Veronica Iacovacci and Mohammad Hasan Dad Ansari and Arianna Menciassi},

url = {https://doi.org/10.1038/s41598-021-02553-z},

doi = {10.1038/s41598-021-02553-z},

issn = {2045-2322},

year  = {2021},

date = {2021-12-01},

journal = {Scientific Reports},

volume = {11},

number = {1},

pages = {23239},

abstract = {Microrobots (MRs) have attracted significant interest for their potentialities in diagnosis and non-invasive intervention in hard-to-reach body areas. Fine control of biomedical MRs requires real-time feedback on their position and configuration. Ultrasound (US) imaging stands as a mature and advantageous technology for MRs tracking, but it suffers from disturbances due to low contrast resolution. To overcome these limitations and make US imaging suitable for monitoring and tracking MRs, we propose a US contrast enhancement mechanism for MR visualization in echogenic backgrounds (e.g., tissue). Our technique exploits the specific acoustic phase modulation produced by the MR characteristic motions. By applying this principle, we performed real-time visualization and position tracking of a magnetic MR rolling on a lumen boundary, both in static flow and opposing flow conditions, with an average error of 0.25 body-lengths. Overall, the reported results unveil countless possibilities to exploit the proposed approach as a robust feedback strategy for monitoring and tracking biomedical MRs in-vivo.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ramesh2021,

title = {Multi-task temporal convolutional networks for joint recognition of surgical phases and steps in gastric bypass procedures},

author = {Sanat Ramesh and Diego Dall'Alba and Cristians Gonzalez and Tong Yu and Pietro Mascagni and Didier Mutter and Jacques Marescaux and Paolo Fiorini and Nicolas Padoy},

url = {https://doi.org/10.1007/s11548-021-02388-z},

doi = {10.1007/s11548-021-02388-z},

year  = {2021},

date = {2021-05-01},

journal = {International Journal of Computer Assisted Radiology and Surgery},

publisher = {Springer Science and Business Media LLC},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{finocchiaro2021training,

title = {Training Simulators for Gastrointestinal Endoscopy: Current and Future Perspectives},

author = {Martina Finocchiaro and Pablo Cortegoso Valdivia and Albert Hernansanz and Nicola Marino and Denise Amram and Alicia Casals and Arianna Menciassi and Wojciech Marlicz and Gastone Ciuti and Anastasios Koulaouzidis},

url = {https://www.mdpi.com/2072-6694/13/6/1427},

year  = {2021},

date = {2021-01-01},

journal = {Cancers},

volume = {13},

number = {6},

pages = {1427},

publisher = {Multidisciplinary Digital Publishing Institute},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{li2021path,

title = {Path planning for endovascular catheterization under curvature constraints via two-phase searching approach},

author = {Zhen Li and Jenny Dankelman and Elena De Momi},

url = {https://doi.org/10.1007/s11548-021-02328-x},

doi = {10.1007/s11548-021-02328-x},

year  = {2021},

date = {2021-01-01},

journal = {International Journal of Computer Assisted Radiology and Surgery},

volume = {16},

number = {4},

pages = {619--627},

publisher = {Springer},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{lazo2021using,

title = {Using spatial-temporal ensembles of convolutional neural networks for lumen segmentation in ureteroscopy},

author = {Jorge F. Lazo and Aldo Marzullo and Sara Moccia and Michele Catellani and Benoit Rosa and Michel Mathelin and Elena De Momi},

url = {https://link.springer.com/article/10.1007/s11548-021-02376-3},

year  = {2021},

date = {2021-01-01},

journal = {International journal of computer assisted radiology and surgery},

volume = {16},

number = {6},

pages = {915--922},

publisher = {Springer},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{CulmoneYikilmazTrauzettelBreedveld2021,

title = {Follow-The-Leader Mechanisms in Medical Devices: A Review on Scientific and Patent Literature},

author = {Costanza Culmone and Semih Fatih Yikilmaz and Fabian Trauzettel and Paul Breedveld},

url = {https://atlas-itn.eu/wp-content/uploads/2022/01/Culmone-Yikilmaz-Trauzettel_2021.pdf},

doi = {10.1109/RBME.2021.3113395},

year  = {2021},

date = {2021-01-01},

journal = {IEEE Reviews in Biomedical Engineering},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{FarolaBarata2021ILVE,

title = {IVUS-Based Local Vessel Estimation for Robotic Intravascular Navigation},

author = {Beatriz {Farola Barata} and Phuong Toan Tran and Gianni Borghesan and Keir McCutcheon and Diego Dall'Alba and Paolo Fiorini and Jos {Vander Sloten} and Emmanuel {Vander Poorten}},

url = {https://atlas-itn.eu/wp-content/uploads/2021/09/Farola-Barata_IVUS-Based-Local-Vessel-Estimation-for-Robotic-Intravascular-Navigation_RAL_2021.pdf},

issn = {2377-3766},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {IEEE Robotics and Automation Letters},

volume = {6},

number = {4},

pages = {8102--8109},

publisher = {Institute of Electrical and Electronics Engineers},

abstract = {Intra-operative local 3D vessel representations have the potential to significantly decrease the use of contrast agents and exposure to ionizing radiation during endovascular procedures, while overcoming the 2D visualization limitation of fluoroscopic guidance. By fusing intravascular ultrasound (IVUS) imaging and electromagnetic (EM) pose sensing in a robotic catheter tip, a real-time local 3D model of the vasculature could be constructed intra-operatively. This letter proposes the use of a cylinder model to approximate the vessel geometry near the catheter tip. An unscented Kalman filter is employed to robustly estimate the cylinder that best fits IVUS and EM data while navigating through the vessel. This forms a radiation-free alternative to conventional radiation-based guidance. Validation on one in silico and two in vitro models showed median estimation errors of cylinder radius of 0.14 mm, 0.42 mm and 0.70 mm; cylinder position of 0.45 mm, 1.07 mm and 0.96 mm; and cylinder orientation of 2.94°, 4.60° and 3.03° showing great potential for helping interventionists preventing harmful interactions between the instrument tip and the vessel wall.

},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{9411924,

title = {A Lumen Segmentation Method in Ureteroscopy Images based on a Deep Residual U-Net architecture},

author = {Jorge F. Lazo and Aldo Marzullo and Sara Moccia and Michele Catellani and Benoit Rosa and Francesco Calimeri and Michel Mathelin and Elena De Momi},

doi = {10.1109/ICPR48806.2021.9411924 URL=https://arxiv.org/pdf/2101.05021.pdf},

year  = {2021},

date = {2021-01-01},

booktitle = {2020 25th International Conference on Pattern Recognition (ICPR)},

pages = {9203-9210},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.3389/frobt.2021.758411,

title = {Shape Reconstruction Processes for Interventional Application Devices: State of the Art, Progress, and Future Directions},

author = {Sujit Kumar Sahu and Canberk Sozer and Benoit Rosa and Izadyar Tamadon and Pierre Renaud and Arianna Menciassi},

url = {https://www.frontiersin.org/article/10.3389/frobt.2021.758411},

doi = {10.3389/frobt.2021.758411},

issn = {2296-9144},

year  = {2021},

date = {2021-01-01},

journal = {Frontiers in Robotics and AI},

volume = {8},

abstract = {Soft and continuum robots are transforming medical interventions thanks to their flexibility, miniaturization, and multidirectional movement abilities. Although flexibility enables reaching targets in unstructured and dynamic environments, it also creates challenges for control, especially due to interactions with the anatomy. Thus, in recent years lots of efforts have been devoted for the development of shape reconstruction methods, with the advancement of different kinematic models, sensors, and imaging techniques. These methods can increase the performance of the control action as well as provide the tip position of robotic manipulators relative to the anatomy. Each method, however, has its advantages and disadvantages and can be worthwhile in different situations. For example, electromagnetic (EM) and Fiber Bragg Grating (FBG) sensor-based shape reconstruction methods can be used in small-scale robots due to their advantages thanks to miniaturization, fast response, and high sensitivity. Yet, the problem of electromagnetic interference in the case of EM sensors, and poor response to high strains in the case of FBG sensors need to be considered. To help the reader make a suitable choice, this paper presents a review of recent progress on shape reconstruction methods, based on a systematic literature search, excluding pure kinematic models. Methods are classified into two categories. First, sensor-based techniques are presented that discuss the use of various sensors such as FBG, EM, and passive stretchable sensors for reconstructing the shape of the robots. Second, imaging-based methods are discussed that utilize images from different imaging systems such as fluoroscopy, endoscopy cameras, and ultrasound for the shape reconstruction process. The applicability, benefits, and limitations of each method are discussed. Finally, the paper draws some future promising directions for the enhancement of the shape reconstruction methods by discussing open questions and alternative methods.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ha2021robust,

title = {Robust catheter tracking by fusing electromagnetic tracking, fiber bragg grating and sparse fluoroscopic images},

author = {HA, Xuan Thao and Mouloud Ourak and Omar Al-Ahmad and Di Wu and Gianni Borghesan and Arianna Menciassi and Emmanuel Vander Poorten},

url = {https://atlas-itn.eu/wp-content/uploads/2021/08/RobustCatheterTracking_techrvix.pdf},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {IEEE Sensors Journal},

volume = {21},

number = {20},

pages = {23422--23434},

publisher = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Wu2021,

title = {Hysteresis modeling of robotic catheters based on long short-term memory network for improved environment reconstruction},

author = {Di Wu and Yao Zhang and Mouloud Ourak and Kenan Niu and Jenny Dankelman and Emmanuel Vander Poorten},

url = {https://atlas-itn.eu/wp-content/uploads/2021/07/RG_LSTM-1.pdf},

year  = {2021},

date = {2021-01-01},

journal = {IEEE Robotics and Automation Letters},

volume = {6},

number = {2},

pages = {2106--2113},

publisher = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ourak2021fusion,

title = {Fusion of Biplane Fluoroscopy with Fiber Bragg Grating for 3D Catheter Shape Reconstruction},

author = {Mouloud Ourak and Stijn De Buck and Ha, Xuan Thao and Omar Al-Ahmad and Kobe Bamps and Joris Ector and Vander Poorten, Emmanuel },

url = {https://atlas-itn.eu/wp-content/uploads/2022/01/RAL_FusionofBiplaneFluoroscopy.pdf},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {IEEE Robotics and Automation Letters},

volume = {6},

number = {4},

pages = {6505--6512},

publisher = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{sestini2021kinematic,

title = {A Kinematic Bottleneck Approach For Pose Regression of Flexible Surgical Instruments directly from Images},

author = {Luca Sestini and Benoit Rosa and Elena De Momi and Giancarlo Ferrigno and Nicolas Padoy},

url = {https://arxiv.org/pdf/2103.00586.pdf},

doi = {10.1109/LRA.2021.3062308},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {IEEE Robotics and Automation Letters},

volume = {6},

number = {2},

pages = {2938--2945},

publisher = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{zulina2021colon,

title = {Colon phantoms with cancer lesions for endoscopic characterization with optical coherence tomography},

author = {Natalia Zulina and Oscar Caravaca and Guiqiu Liao and Sara Gravelyn and Morgane Schmitt and Keshia Badu and Lucile Heroin and Michalina J Gora},

url = {https://doi.org/10.1364/BOE.402081},

year  = {2021},

date = {2021-01-01},

journal = {Biomedical optics express},

volume = {12},

number = {2},

pages = {955--968},

publisher = {Optical Society of America},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{liao2021data,

title = {Data Stream Stabilization for Optical Coherence Tomography Volumetric Scanning},

author = {Guiqiu Liao and Oscar Caravaca-Mora and Benoit Rosa and Philippe Zanne and Alexandre Asch and Diego Dall’Alba and Paolo Fiorini and Michel Mathelin and Florent Nageotte and Michalina J Gora},

url = {https://atlas-itn.eu/wp-content/uploads/2021/12/Data_Stream_Stabilization_for_Optical_Coherence_Tomography_Volumetric_Scanning.pdf},

year  = {2021},

date = {2021-01-01},

journal = {IEEE Transactions on Medical Robotics and Bionics},

volume = {3},

number = {4},

pages = {855--865},

publisher = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {article}

}