55 research outputs found
Context-aware learning for robot-assisted endovascular catheterization
Endovascular intervention has become a mainstream treatment of cardiovascular diseases. However, multiple challenges remain such as unwanted radiation exposures, limited two-dimensional image guidance, insufficient force perception and haptic cues. Fast evolving robot-assisted platforms improve the stability and accuracy of instrument manipulation. The master-slave system also removes radiation to the operator. However, the integration of robotic systems into the current surgical workflow is still debatable since repetitive, easy tasks have little value to be executed by the robotic teleoperation. Current systems offer very low autonomy, potential autonomous features could bring more benefits such as reduced cognitive workloads and human error, safer and more consistent instrument manipulation, ability to incorporate various medical imaging and sensing modalities. This research proposes frameworks for automated catheterisation with different machine learning-based algorithms, includes Learning-from-Demonstration, Reinforcement Learning, and Imitation Learning. Those frameworks focused on integrating context for tasks in the process of skill learning, hence achieving better adaptation to different situations and safer tool-tissue interactions. Furthermore, the autonomous feature was applied to next-generation, MR-safe robotic catheterisation platform. The results provide important insights into improving catheter navigation in the form of autonomous task planning, self-optimization with clinical relevant factors, and motivate the design of intelligent, intuitive, and collaborative robots under non-ionizing image modalities.Open Acces
End-to-End Real-time Catheter Segmentation with Optical Flow-Guided Warping during Endovascular Intervention
Accurate real-time catheter segmentation is an important pre-requisite for
robot-assisted endovascular intervention. Most of the existing learning-based
methods for catheter segmentation and tracking are only trained on small-scale
datasets or synthetic data due to the difficulties of ground-truth annotation.
Furthermore, the temporal continuity in intraoperative imaging sequences is not
fully utilised. In this paper, we present FW-Net, an end-to-end and real-time
deep learning framework for endovascular intervention. The proposed FW-Net has
three modules: a segmentation network with encoder-decoder architecture, a flow
network to extract optical flow information, and a novel flow-guided warping
function to learn the frame-to-frame temporal continuity. We show that by
effectively learning temporal continuity, the network can successfully segment
and track the catheters in real-time sequences using only raw ground-truth for
training. Detailed validation results confirm that our FW-Net outperforms
state-of-the-art techniques while achieving real-time performance.Comment: ICRA 202
Toward a Versatile Robotic Platform for Fluoroscopy and MRI-Guided Endovascular Interventions:A Pre-Clinical Study
Cardiovascular diseases are the most common cause of death worldwide. Remotely manipulated robotic systems are utilized to perform minimally invasive endovascular interventions. The main benefits of this methodology are reduced recovery time, improvement of clinical skills and procedural facilitation. Currently, robotic assistance, precision, and stability of instrument manipulation are compensated by the lack of haptic feedback and an excessive amount of radiation to the patient. This paper proposes a novel master-slave robotic platform that aims to bring the haptic feedback benefit on the master side, providing an intuitive user interface, and clinical familiar workflow. The slave robot is capable of manipulating conventional catheters and guidewires in multi-modal imaging environments. The system has been initially tested in a phantom cannulation study under fluoroscopic guidance, evaluating its reliability and procedural protocol. As the slave robot has been entirely produced by additive manufacturing and using pneumatic actuation, MR compatibility is enabled and was evaluated in a preliminary study. Results of both studies strongly support the applicability of the robot in different imaging environments and prospective clinical translation
Large-Scale Comparative Analyses of Tick Genomes Elucidate Their Genetic Diversity and Vector Capacities
Effects of dietary methionine on growth performance and metabolism through modulating nutrient-related pathways in largemouth bass (Micropterus salmoides)
Methionine (Met) as molecular signaling plays a vital regulatory role in growth-related cellular functions. However, more research in the regulatory mechanism of Met in fish species is needed. Therefore, this study was designed to elucidate the regulatory role of dietary Met on body growth performance and metabolism. Largemouth bass (initial body weight: 4.10 ± 0.01 g) fed with control (CON, Met: 1.21 % of diet) diet and Met deficiency (MD, Met: 0.93 % of diet) diet, respectively for 8 weeks. Results of present study showed that compared with the MD diet (specific growth performance: 3.01 ± 0.03 %/d; weight gain ratio: 438 ± 9.16 %), control diet significantly increased the specific growth performance (3.36 ± 0.02 %/d) and weight gain ratio (557 ± 7.41 %), respectively (P < 0.05). Moreover, the fish fed with control diet also had higher feed efficient ratio and protein efficiency ratio (1.12 ± 0.01; 2.28 ± 0.01) than the fish fed with MD diet (0.88 ± 0.03; 1.83 ± 0.05). Mechanically, present study demonstrated that Met supplementation increased the amino acid (AA) concentrations through improving transport efficiency of AA transporters. Elevated AA concentrations promoted systemic nutrient sensing by activating the growth hormone-insulin-like growth factor (GH-IGF) signaling pathway. Activated GH-IGF signaling then up-regulated the target of rapamycin (TOR) signaling and suppressed the amino acids response (AAR) signaling. Up-regulated TOR and down-regulated AAR caused by Met supplementation acted together to increase the nutrient metabolic level, which further accelerate the growth performance. Our study better explained how fish through nutrient sensing signaling to coordinating growth and metabolism in response to dietary Met availability
Asymmetric domino heck arylation and alkylation of nonconjugated dienes : double C–F···sodium attractive noncovalent interaction
Palladium catalyzes a domino Heck arylation and alkylation of nonconjugated cyclodienes to produce trans isomers of disubstituted cyclohexenes in exceptionally high enantiomeric ratios, reaching 100:1 to 200:1 in many cases. Importantly, the interactions of the two CF bonds of Josiphos and the sodium ion of malonates facilitates stereoselective allylic attack through DFT calculations and experiments. This is a new type of attractive noncovalent interactions found in organometallic catalysis.Economic Development Board (EDB)Nanyang Technological UniversityWe acknowledge financial support from Peking University Shenzhen Graduate School and Shenzhen Bay Laboratory for J.S.Z.; the National Natural Science Foundation of China (NSFC 21933004) for Y.-D.W.; Nanyang Technological University and GlaxoSmithKline and the Singapore Economic Development Board Trust Fund (2017 GSK-EDB Green & Sustainable Manufacturing Award) for Y.R.C
Enantioselective intermolecular Heck and reductive Heck reactions of aryl triflates, mesylates, and tosylates catalyzed by nickel
Nickel-catalyzed intermolecular Heck reaction of cycloalkenes proceeds well with aryl triflates, mesylates and tosylates in excellent enantiomeric ratios. The asymmetric reductive Heck reaction also works with a 2-cyclopentenone ketal, which is equivalent to conjugate arylation of the enone itself.Economic Development Board (EDB)Accepted versionWe acknowledge financial supports from Peking University Shenzhen Graduate School, Shenzhen Bay Laboratory Insti- tute of Chemical Biology, Nanyang Technological University, GlaxoSmithKline and the Singapore Economic Development Board Trust Fund (2017 GSK-EDB Green and Sustainable Manufacturing Award) and A*STAR Science and Engineer- ing Research Council (A1783c0010)
In-vivo Validation of a Novel Robotic Platform for Endovascular Intervention
Objective: In-vivo validation on animal setting of a pneumatically propelled robot for endovascular intervention, to determine safety and clinical advantage of robotic cannulations compared to manual operation. Methods: Robotic assistance and image-guided intervention are increasingly used for improving endovascular procedures with enhanced navigation dexterity and accuracy. However, most platforms developed in the past decade still present inherent limitations in terms of altered clinical workflow, counterintuitive human-robot interaction, and a lack of versatility. We have created a versatile, highly integrated platform for robot-assisted endovascular intervention aimed at addressing such limitations, and here we demonstrate its clinical usability through in-vivo animal trials. A detailed in-vivo study on four porcine models conducted with our robotic platform is reported, involving cannulation and balloon angioplasty of five target arteries. Results: The trials showed a 100% success rate, and post-mortem histopathological assessment demonstrated a reduction in the incidence and severity of vessel trauma with robotic navigation versus manual manipulation. Conclusion: In-vivo experiments demonstrated that the applicability of our robotic system within the context of this study was well tolerated, with good feasibility, and low risk profile. Comparable results were observed with robotics and manual cannulation, with clinical outcome potentially in favor of robotics. Significance: This study showed that the proposed robotic platform can potentially improve the execution of endovascular procedures, paving the way for clinical translation
Toward a Versatile Robotic Platform for Fluoroscopy and MRI-Guided Endovascular Interventions: A Pre-Clinical Study
Cardiovascular diseases are the most common cause of death worldwide. Remotely manipulated robotic systems are utilized to perform minimally invasive endovascular interventions. The main benefits of this methodology are reduced recovery time, improvement of clinical skills and procedural facilitation. Currently, robotic assistance, precision, and stability of instrument manipulation are compensated by the lack of haptic feedback and an excessive amount of radiation to the patient. This paper proposes a novel master-slave robotic platform that aims to bring the haptic feedback benefit on the master side, providing an intuitive user interface, and clinical familiar workflow. The slave robot is capable of manipulating conventional catheters and guidewires in multi-modal imaging environments. The system has been initially tested in a phantom cannulation study under fluoroscopic guidance, evaluating its reliability and procedural protocol. As the slave robot has been entirely produced by additive manufacturing and using pneumatic actuation, MR compatibility is enabled and was evaluated in a preliminary study. Results of both studies strongly support the applicability of the robot in different imaging environments and prospective clinical translation
- …