Convolutional Neural Networks (CNNs) can achieve excellent computer-assisted diagnosis performance, relying on sufficient annotated training data. Unfortunately, most medical imaging datasets, often collected from var...
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This paper presented the calibration of the nanorobotic manipulator inside Scanning Electron Microscope (SEM). Repeating movement is frequently happing to reach the predetermined position and in order to realize the a...
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ISBN:
(纸本)9781538604915
This paper presented the calibration of the nanorobotic manipulator inside Scanning Electron Microscope (SEM). Repeating movement is frequently happing to reach the predetermined position and in order to realize the automated nanomanipulation inside SEM, the errors of the nanomanipultor and the system must be analyzed. A series of experiments based on SEM image feedback were conducted and the end-effectors can characterize the relationship of the two axis. An atomic force microscope (AFM) cantilever was assembled on the top of the nanorobotic manipulator, which moved straightly along the X or Y axis under stable speed. Through SEM video stream, a image processing method was used to analyze the errors of the nanomanipultor and the thermal drift of the encoder. The movement of nanomanipultor presented the good linearity and the error between the platform and the image coordinates were deteced. The slope of the x-direction is less than 1.7° and the slope of the y-direction is less than 0.8°. The nanomanipultor corrected his own track until the drift error is accumulated to 260 nm.
Computational competitions are the standard for benchmarking medical image analysis algorithms, but they typically use small curated test datasets acquired at a few centers, leaving a gap to the reality of diverse mul...
Computational competitions are the standard for benchmarking medical image analysis algorithms, but they typically use small curated test datasets acquired at a few centers, leaving a gap to the reality of diverse multicentric patient data. To this end, the Federated Tumor Segmentation (FeTS) Challenge represents the paradigm for real-world algorithmic performance evaluation. The FeTS challenge is a competition to benchmark (i) federated learning aggregation algorithms and (ii) state-of-the-art segmentation algorithms, across multiple international sites. Weight aggregation and client selection techniques were compared using a multicentric brain tumor dataset in realistic federated learning simulations, yielding benefits for adaptive weight aggregation, and efficiency gains through client sampling. Quantitative performance evaluation of state-of-the-art segmentation algorithms on data distributed internationally across 32 institutions yielded good generalization on average, albeit the worst-case performance revealed data-specific modes of failure. Similar multi-site setups can help validate the real-world utility of healthcare AI algorithms in the future.
The Particle Swarm Optimization (PSO) algorithm is a population-based metaheuristics in which the individuals communicate through decentralized networks. The network can be of many forms but traditionally its structur...
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Simulation environments for Unmanned Aerial Vehicles (UAVs) can be very useful for prototyping user interfaces and training personnel that will operate UAVs in the real world. The realistic operation of such simulatio...
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Traditional methods of Robot teaching require human demonstrators to program with a teaching pendant,which is a complex and time-consuming *** this paper,we propose a novel method based on teleoperation which allows a...
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Traditional methods of Robot teaching require human demonstrators to program with a teaching pendant,which is a complex and time-consuming *** this paper,we propose a novel method based on teleoperation which allows a demonstrator to train robot in an intuitive *** specifically,at the beginning the demonstrator controls a robot by visual *** then a learning algorithm based on radial basis function(RBF) network is used to transfer the demonstrator's motions to the *** verify the effectiveness of this developed methods,several simulation experiments have been carried out which based on Microsoft Kinect Sensor and the Virtual Robot Experimentation Platform(V-REP).The experimental results show that this method has achieved satisfactory *** the help of this method,the robot can not only complete the task autonomously after teaching,but also can learn the details of demonstrator's behavior.
This paper studies the problem of image-based leader-follower formation control for mobile robots, where the controller is designed independently of the leader's motion. An adaptive control scheme, which is suitab...
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In the gastrointestinal (GI) tract endoscopy field, ingestible wireless capsule endoscopy is emerging as a novel, minimally invasive diagnostic technology for inspection of the GI tract and diagnosis of a wide range o...
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This paper studies a green paradigm for the underlay coexistence of primary users (PUs) and secondary users (SUs) in energy harvesting cognitive radio networks (EH-CRNs), wherein battery-free SUs capture both the spec...
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