scholarly journals Real-time determination of sarcomere length of a single cardiomyocyte during contraction

2013 ◽  
Vol 304 (6) ◽  
pp. C519-C531 ◽  
Author(s):  
Pearu Peterson ◽  
Mari Kalda ◽  
Marko Vendelin
Keyword(s):  
Real Time ◽  
Sarcomere Length ◽  
Accurate Determination ◽  
Region Of Interest ◽  
Estimation Procedure ◽  
Accurate Method ◽  
Estimation Accuracy ◽  
Rat Cardiomyocytes ◽  
Image Pixels ◽  
Microscopy Images

Sarcomere length of a cardiomyocyte is an important control parameter for physiology studies on a single cell level; for instance, its accurate determination in real time is essential for performing single cardiomyocyte contraction experiments. The aim of this work is to develop an efficient and accurate method for estimating a mean sarcomere length of a contracting cardiomyocyte using microscopy images as an input. The novelty in developed method lies in 1) using unbiased measure of similarities to eliminate systematic errors from conventional autocorrelation function (ACF)-based methods when applied to region of interest of an image, 2) using a semianalytical, seminumerical approach for evaluating the similarity measure to take into account spatial dependence of neighboring image pixels, and 3) using a detrend algorithm to extract the sarcomere striation pattern content from the microscopy images. The developed sarcomere length estimation procedure has superior computational efficiency and estimation accuracy compared with the conventional ACF and spectral analysis-based methods using fast Fourier transform. As shown by analyzing synthetic images with the known periodicity, the estimates obtained by the developed method are more accurate at the subpixel level than ones obtained using ACF analysis. When applied in practice on rat cardiomyocytes, our method was found to be robust to the choice of the region of interest that may 1) include projections of carbon fibers and nucleus, 2) have uneven background, and 3) be slightly disoriented with respect to average direction of sarcomere striation pattern. The developed method is implemented in open-source software.

Augmented Reality Overlay System for Computer-guided Needle Procedures

1969 ◽  
Author(s):  
Zachary Baum
Keyword(s):  
Augmented Reality ◽  
Real Time ◽  
Region Of Interest ◽  
Calibration Method ◽  
Position Error ◽  
Ct Image ◽  
Entire System ◽  
Projected Image ◽  
Needle Interventions

Purpose: Augmented reality overlay systems can be used to project a CT image directly onto a patient during procedures. They have been actively trialed for computer-guided procedures, however they have not become commonplace in practice due to restrictions of previous systems. Previous systems have not been handheld, and have had complicated calibration procedures. We put forward a handheld tablet-based system for assisting with needle interventions. Methods: The system consists of a tablet display and a 3-D printed reusable and customizable frame. A simple and accurate calibration method was designed to align the patient to the projected image. The entire system is tracked via camera, with respect to the patient, and the projected image is updated in real time as the system is moved around the region of interest. Results: The resulting system allowed for 0.99mm mean position error in the plane of the image, and a mean position error of 0.61mm out of the plane of the image. This accuracy was thought to be clinically acceptable for tool using computer-guidance in several procedures that involve musculoskeletal needle placements. Conclusion: Our calibration method was developed and tested using the designed handheld system. Our results illustrate the potential for the use of augmented reality handheld systems in computer-guided needle procedures. 

scholarly journals Real-Time Runway Detection for Infrared Aerial Image Using Synthetic Vision and an ROI Based Level Set Method

2018 ◽  
Vol 10 (10) ◽  
pp. 1544 ◽  
Author(s):  
Changjiang Liu ◽  
Irene Cheng ◽  
Anup Basu
Keyword(s):  
Real Time ◽  
Level Set Method ◽  
Level Set ◽  
Infrared Image ◽  
Region Of Interest ◽  
Aerial Image ◽  
Real Time Processing ◽  
Synthetic Vision ◽  
Level Set Function ◽  
Rough Region

We present a new method for real-time runway detection embedded in synthetic vision and an ROI (Region of Interest) based level set method. A virtual runway from synthetic vision provides a rough region of an infrared runway. A three-thresholding segmentation is proposed following Otsu’s binarization method to extract a runway subset from this region, which is used to construct an initial level set function. The virtual runway also gives a reference area of the actual runway in an infrared image, which helps us design a stopping criterion for the level set method. In order to meet the needs of real-time processing, the ROI based level set evolution framework is implemented in this paper. Experimental results show that the proposed algorithm is efficient and accurate.

scholarly journals Isolation and molecular characterization of Mycobacterium tuberculosis complex isolated from raw milk in some dairy farms in Egypt

2016 ◽  
Vol 5 (2) ◽  
pp. 105
Author(s):  
Heba Hussien ◽  
Eman Mahrous
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Real Time ◽  
Real Time Pcr ◽  
Culture Method ◽  
Raw Milk ◽  
Accurate Method ◽  
Tuberculosis Complex ◽  
Milk Samples ◽  
Source Of Infection

<p>This study was conducted to detect <em>Mycobacterium tuberculosis</em> complex in milk in three Egyptian Governorates; El-Sharkia, El-Menoufia and El-Behera Governorates. 300 milk samples were collected from tuberculin positive cases, 18 (6.0%) were shedding <em>Mycobacterium tuberculosis</em> complex in their milk which detected by real time PCR. On another hand, 170 milk samples were collected from tuberculin negative cases, 5 (2.9%) were shedding <em>Mycobacterium tuberculosis</em> complex in their milk which detected by real time PCR. All milk samples were examined by three techniques including Microscopic examination, culture and real time PCR. Real time PCR is more rapid and accurate method than microscopic and culture method. The isolated colonies from culture were examined by Multiplex PCR to demonstrate the source of infection either human or animal source.</p>

scholarly journals Learning-Type Anchors-Driven Pose Estimation for the Autolanding Fixed-Wing UAVs

2021 ◽  
Author(s):  
Dengqing Tang ◽  
Lincheng Shen ◽  
Xiaojiao Xiang ◽  
Han Zhou ◽  
Tianjiang Hu
Keyword(s):  
Real Time ◽  
Pose Estimation ◽  
Stereo Vision ◽  
Vision System ◽  
Estimation Method ◽  
Satellite System ◽  
Training Dataset ◽  
Estimation Accuracy ◽  
The Impact ◽  
Outdoor Experiments

<p>We propose a learning-type anchors-driven real-time pose estimation method for the autolanding fixed-wing unmanned aerial vehicle (UAV). The proposed method enables online tracking of both position and attitude by the ground stereo vision system in the Global Navigation Satellite System denied environments. A pipeline of convolutional neural network (CNN)-based UAV anchors detection and anchors-driven UAV pose estimation are employed. To realize robust and accurate anchors detection, we design and implement a Block-CNN architecture to reduce the impact of the outliers. With the basis of the anchors, monocular and stereo vision-based filters are established to update the UAV position and attitude. To expand the training dataset without extra outdoor experiments, we develop a parallel system containing the outdoor and simulated systems with the same configuration. Simulated and outdoor experiments are performed to demonstrate the remarkable pose estimation accuracy improvement compared with the conventional Perspective-N-Points solution. In addition, the experiments also validate the feasibility of the proposed architecture and algorithm in terms of the accuracy and real-time capability requirements for fixed-wing autolanding UAVs.</p>

scholarly journals Determinants of Real-Time fMRI Neurofeedback Performance and Improvement – a Machine Learning Mega-Analysis

2020 ◽  
Author(s):  
Amelie Haugg ◽  
Fabian M. Renz ◽  
Andrew A. Nicholson ◽  
Cindy Lor ◽  
Sebastian J. Götzendorfer ◽  
...  
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Clinical Symptoms ◽  
Gain Control ◽  
Region Of Interest ◽  
Open Science ◽  
Imagery Task ◽  
Neurofeedback Training ◽  
Brain Signals ◽  
Healthy Participants

AbstractReal-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinical symptoms in patient populations. However, a considerably large ratio of participants undergoing neurofeedback training do not learn to control their own brain signals and, consequently, do not benefit from neurofeedback interventions, which limits clinical efficacy of neurofeedback interventions. As neurofeedback success varies between studies and participants, it is important to identify factors that might influence neurofeedback success. Here, for the first time, we employed a big data machine learning approach to investigate the influence of 20 different design-specific (e.g. activity vs. connectivity feedback), region of interest-specific (e.g. cortical vs. subcortical) and subject-specific factors (e.g. age) on neurofeedback performance and improvement in 608 participants from 28 independent experiments.With a classification accuracy of 60% (considerably different from chance level), we identified two factors that significantly influenced neurofeedback performance: Both the inclusion of a pre-training no-feedback run before neurofeedback training and neurofeedback training of patients as compared to healthy participants were associated with better neurofeedback performance. The positive effect of pre-training no-feedback runs on neurofeedback performance might be due to the familiarization of participants with the neurofeedback setup and the mental imagery task before neurofeedback training runs. Better performance of patients as compared to healthy participants might be driven by higher motivation of patients, higher ranges for the regulation of dysfunctional brain signals, or a more extensive piloting of clinical experimental paradigms. Due to the large heterogeneity of our dataset, these findings likely generalize across neurofeedback studies, thus providing guidance for designing more efficient neurofeedback studies specifically for improving clinical neurofeedback-based interventions. To facilitate the development of data-driven recommendations for specific design details and subpopulations the field would benefit from stronger engagement in Open Science and data sharing.

scholarly journals Investigation of accurate method in 3-D position using Cors-Net in Istanbul

2012 ◽  
Vol 18 (2) ◽  
pp. 171-184 ◽  
Author(s):  
Kutalmis Gumus ◽  
Cahit Tagi Celik ◽  
Halil Erkaya
Keyword(s):  
Real Time ◽  
Conventional Method ◽  
Global Positioning System ◽  
Complex Structure ◽  
Accurate Method ◽  
Reference Station ◽  
Positioning System ◽  
Virtual Reference ◽  
Global Positioning ◽  
Set Up

In this study, for Istanbul, there are two Cors Networks (Cors-TR, Iski Cors) providing Virtual Reference Station (VRS), and Flachen Korrektur Parameter (FKP), corrections to rover receiver for determining 3-D positions in real time by Global Positioning System (GPS). To determine which method (or technique) provides accurate method for position fixing, a test network consisting of 49 stations was set up in Yildiz Technical University Davudpasa Campus. The coordinates of the stations in the test network were determined by conventional geodetic, classical RTK, VRS and FKP methods serviced by both Cors-TR and Iski Cors. The results were compared to the coordinates by the conventional method by using total station. The results showed a complex structure as the accuracy differs from one component to another such as in horizontal coordinates, Y components by CorsTR_VRS and Cors_TR_ FKP showed 'best' results while the same technique provided X components consistent accuracy with the Y component but less accurate than by real time kinematic (RTK). In vertical components, of all the techniques used for the h components, CorsTR_VRS showed 'best' accuracy with three outliers.

scholarly journals Left Bundle Branch Area Pacing guided by Continuous Uninterrupted Monitoring of the unipolar Pacing Characteristics.

2021 ◽  
Author(s):  
Kris Gillis ◽  
Jean-Yves Wielandts ◽  
Gabriela Hilfiker ◽  
Louisa O'Neill ◽  
Alina Vlase ◽  
...  
Keyword(s):  
Real Time ◽  
Group Performance ◽  
Accurate Determination ◽  
Septal Perforation ◽  
Validation Group ◽  
Pacing Lead ◽  
Qrs Morphology ◽  
Qrs Duration ◽  
Highly Correlated

Introduction. During left bundle branch area pacing (LBBAP) lead implantation, intermittent monitoring of unipolar pacing characteristics validates LBB capture and can detect septal perforation. We aimed to demonstrate that continuous uninterrupted unipolar pacing from an inserted lead stylet (LS) is feasible and facilitates LBBAP implantation. Methods. Thirty patients (mean age 76 ± 14 years) were implanted with stylet-driven pacing lead (Biotronik Solia S60). In 10 patients (validation-group) conventional, interrupted implantation was performed, with comparison of unipolar pacing characteristics between LS and connector-pin (CP)-pacing after each rotation step. In 20 patients (feasibility-group) performance and safety of uninterrupted implantation during continuous pacing from the LS were analyzed. Results. In the validation-group, LS and CP-pacing impedances were highly correlated (R=0.95, p<0.0001, bias 12±37Ω). Pacing characteristics from LS and CP showed comparable sensed electrograms and paced QRS morphologies. In the feasibility-group, continuous LS-pacing allowed beat-to-beat monitoring of impedance and QRS morphology to guide implantation. This resulted in successful LBBAP in all patients, after a mean of 1±0 attempts, with mean threshold 0.81 ± 0.4V, median sensing 6.5mV [IQR 4.4-9.5] and mean impedance 624 ± 101Ω, and positive LBBAP-criteria with median paced QRS duration 120ms [IQR 112-152ms] and median pLVAT 73ms [IQR 68-80.5ms]. No septal perforation occurred. Conclusion. Unipolar pacing from the LS allows accurate determination of pacing impedance and generates similar paced QRS morphologies and equal sensed electrograms, compared to CP pacing. Continuous LS pacing allows real-time monitoring of impedance and paced QRS morphology, which facilitates a safe and successful LBBAP lead implantation.

Sign in / Sign up

Export Citation Format

Share Document