scholarly journals 3D Shape Estimation Of Tendon-Driven Catheters Using Ultrasound Imaging

2021 ◽  
Author(s):  
Niloufaralsadat Hashemi ◽  
Farrokh Sharifi ◽  
Jahan Tavakkoli
Keyword(s):  
Kalman Filter ◽  
Imaging System ◽  
Imaging Systems ◽  
Computational Time ◽  
Shape Estimation ◽  
Adaptive Kalman Filter ◽  
3D Shape ◽  
Design Time ◽  
Minimally Invasive Surgical ◽  
Estimate Error

Active cable/tendon-driven catheters are becoming an established part of the minimally invasive surgical procedures. Therefore, there has been growing interest in literature in estimating the shape of their distal end especially using clinical ultrasound (US) imaging systems. The purpose of this thesis is to use a B-mode US imaging system to design time-efficient, accurate and robust algorithm for 3D shape estimation of tendon-driven catheters. Kalman filter (KF), Adaptive Kalman filter (AKF) and Particle filter (PF) algorithms were developed for this purpose. First, they were applied to a series of simulated US B-mode images where AKF provided the best estimate (error: 0.2 ± 0.1 mm). Second, they were applied to a series of experimentally obtained US B-mode images. Calibration procedures were carried out to calibrate these US images in the experiment’s workspace. The PF was shown to provide the best 3D shape estimate (error: 8.6 ± 0.1 mm). However, since almost the same accuracy could be achieved with AKF in ten times less computational time, AKF was concluded to be the best method, in terms of accuracy and efficiency, to estimate the 3D shape of tendon-driven catheters.

scholarly journals 3D Shape Estimation Of Tendon-Driven Catheters Using Ultrasound Imaging

2021 ◽  
Author(s):  
Niloufaralsadat Hashemi ◽  
Farrokh Sharifi ◽  
Jahan Tavakkoli
Keyword(s):  
Kalman Filter ◽  
Imaging System ◽  
Imaging Systems ◽  
Computational Time ◽  
Shape Estimation ◽  
Adaptive Kalman Filter ◽  
3D Shape ◽  
Design Time ◽  
Minimally Invasive Surgical ◽  
Estimate Error

Active cable/tendon-driven catheters are becoming an established part of the minimally invasive surgical procedures. Therefore, there has been growing interest in literature in estimating the shape of their distal end especially using clinical ultrasound (US) imaging systems. The purpose of this thesis is to use a B-mode US imaging system to design time-efficient, accurate and robust algorithm for 3D shape estimation of tendon-driven catheters. Kalman filter (KF), Adaptive Kalman filter (AKF) and Particle filter (PF) algorithms were developed for this purpose. First, they were applied to a series of simulated US B-mode images where AKF provided the best estimate (error: 0.2 ± 0.1 mm). Second, they were applied to a series of experimentally obtained US B-mode images. Calibration procedures were carried out to calibrate these US images in the experiment’s workspace. The PF was shown to provide the best 3D shape estimate (error: 8.6 ± 0.1 mm). However, since almost the same accuracy could be achieved with AKF in ten times less computational time, AKF was concluded to be the best method, in terms of accuracy and efficiency, to estimate the 3D shape of tendon-driven catheters.

scholarly journals Sampling Based on Kalman Filter for Shape from Focus in the Presence of Noise

2019 ◽  
Vol 9 (16) ◽  
pp. 3276 ◽  
Author(s):  
Hoon-Seok Jang ◽  
Mannan Saeed Muhammad ◽  
Guhnoo Yun ◽  
Dong Hwan Kim
Keyword(s):  
Kalman Filter ◽  
Signal To Noise Ratio ◽  
Three Dimensional ◽  
Quadratic Function ◽  
Computational Time ◽  
Step Size ◽  
Correlation Peak ◽  
3D Shape ◽  
Shape From Focus ◽  
2D Images

Recovering three-dimensional (3D) shape of an object from two-dimensional (2D) information is one of the major domains of computer vision applications. Shape from Focus (SFF) is a passive optical technique that reconstructs 3D shape of an object using 2D images with different focus settings. When a 2D image sequence is obtained with constant step size in SFF, mechanical vibrations, referred as jitter noise, occur in each step. Since the jitter noise changes the focus values of 2D images, it causes erroneous recovery of 3D shape. In this paper, a new filtering method for estimating optimal image positions is proposed. First, jitter noise is modeled as Gaussian or speckle function, secondly, the focus curves acquired by one of the focus measure operators are modeled as a quadratic function for application of the filter. Finally, Kalman filter as the proposed method is designed and applied for removing jitter noise. The proposed method is experimented by using image sequences of synthetic and real objects. The performance is evaluated through various metrics to show the effectiveness of the proposed method in terms of reconstruction accuracy and computational complexity. Root Mean Square Error (RMSE), correlation, Peak Signal-to-Noise Ratio (PSNR), and computational time of the proposed method are improved on average by about 48%, 11%, 15%, and 5691%, respectively, compared with conventional filtering methods.

Fuzzy adaptive Kalman filter for the drive system with an elastic coupling

2013 ◽  
Vol 62 (2) ◽  
pp. 251-265 ◽  
Author(s):  
Piotr J. Serkies ◽  
Krzysztof Szabat
Keyword(s):  
Kalman Filter ◽  
Control Structure ◽  
Experimental Tests ◽  
Drive System ◽  
Adaptive Kalman Filter ◽  
State Matrix ◽  
State Controller ◽  
Kalman Gain ◽  
Robust Adaptive ◽  
Fuzzy Adaptive

Abstract In the paper issues related to the design of a robust adaptive fuzzy estimator for a drive system with a flexible joint is presented. The proposed estimator ensures variable Kalman gain (based on the Mahalanobis distance) as well as the estimation of the system parameters (based on the fuzzy system). The obtained value of the time constant of the load machine is used to change the values in the system state matrix and to retune the parameters of the state controller. The proposed control structure (fuzzy Kalman filter and adaptive state controller) is investigated in simulation and experimental tests.

EXPRESS: Design Considerations for Discrete Frequency Infrared Microscopy Systems

2021 ◽  
pp. 000370282110133
Author(s):  
Rohit Bhargava ◽  
Yamuna Dilip Phal ◽  
Kevin Yeh
Keyword(s):  
Imaging System ◽  
Chemical Imaging ◽  
Optical Component ◽  
Imaging Systems ◽  
Imaging Data ◽  
Discrete Frequency ◽  
Figures Of Merit ◽  
Design Considerations ◽  
Hardware Implementations ◽  
Measurement Capabilities

Discrete frequency infrared (DFIR) chemical imaging is transforming the practice of microspectroscopy by enabling a diversity of instrumentation and new measurement capabilities. While a variety of hardware implementations have been realized, considerations in the design of all-IR microscopes have not yet been compiled. Here we describe the evolution of IR microscopes, provide rationales for design choices, and the major considerations for each optical component that together comprise an imaging system. We analyze design choices in illustrative examples that use these components to optimize performance, under their particular constraints. We then summarize a framework to assess the factors that determine an instrument’s performance mathematically. Finally, we summarize the design and analysis approach by enumerating performance figures of merit for spectroscopic imaging data that can be used to evaluate the capabilities of imaging systems or suitability for specific intended applications. Together, the presented concepts and examples should aid in understanding available instrument configurations, while guiding innovations in design of the next generation of IR chemical imaging spectrometers.

scholarly journals A new adaptive Kalman filter for navigation systems of carrier-based aircraft

2021 ◽  
Author(s):  
Lifei Zhang ◽  
Shaoping Wang ◽  
Maria Sergeevna Selezneva ◽  
Konstantin Avenirovich Neysipin
Keyword(s):  
Kalman Filter ◽  
Navigation Systems ◽  
Adaptive Kalman Filter
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