scholarly journals A regional bolus tracking and real‐time B 1 calibration method for hyperpolarized 13 C MRI

2018 ◽  
Vol 81 (2) ◽  
pp. 839-851 ◽  
Author(s):  
Shuyu Tang ◽  
Eugene Milshteyn ◽  
Galen Reed ◽  
Jeremy Gordon ◽  
Robert Bok ◽  
...  
Keyword(s):  
Real Time ◽  
Calibration Method ◽  
Bolus Tracking

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. 

Pixel-wise real-time advanced calibration method for thermal infrared cameras

2010 ◽  
Author(s):  
Pierre Tremblay ◽  
Louis Belhumeur ◽  
Martin Chamberland ◽  
André Villemaire ◽  
Patrick Dubois ◽  
...  
Keyword(s):  
Real Time ◽  
Thermal Infrared ◽  
Calibration Method ◽  
Infrared Cameras

scholarly journals Attitude Determination with Magnetometers and Accelerometers to Use in Satellite Simulator

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Helio Koiti Kuga ◽  
Valdemir Carrara
Keyword(s):  
Real Time ◽  
Attitude Control ◽  
Attitude Determination ◽  
Positional Information ◽  
Calibration Method ◽  
Artificial Satellites ◽  
Time Operation ◽  
Determination Process ◽  
Real Time Operation ◽  
Mems Technology

Attitude control of artificial satellites is dependent on information provided by its attitude determination process. This paper presents the implementation and tests of a fully self-contained algorithm for the attitude determination using magnetometers and accelerometers, for application on a satellite simulator based on frictionless air bearing tables. However, it is known that magnetometers and accelerometers need to be calibrated so as to allow that measurements are used to their ultimate accuracy. A calibration method is implemented which proves to be essential for improving attitude determination accuracy. For the stepwise real-time attitude determination, it was used the well-known QUEST algorithm which yields quick response with reduced computer resources. The algorithms are tested and qualified with actual data collected on the streets under controlled situations. For such street runaways, the experiment employs a solid-state magnetoresistive magnetometer and an IMU navigation block consisting of triads of accelerometers and gyros, with MEMS technology. A GPS receiver is used to record positional information. The collected measurements are processed through the developed algorithms, and comparisons are made for attitude determination using calibrated and noncalibrated data. The results show that the attitude accuracy reaches the requirements for real-time operation for satellite simulator platforms.

Integrated real-time polarization image sensor based on UV-NIL and calibration method

2022 ◽  
pp. 1-1
Author(s):  
Chuanlong Guan ◽  
Ran Zhang ◽  
Jinkui Chu ◽  
Ze Liu ◽  
Yuanyi Fan ◽  
...  
Keyword(s):  
Real Time ◽  
Calibration Method ◽  
Image Sensor ◽  
Polarization Image

Real-time self-adaptive calibration method for high speed acquisition system

2019 ◽  
Vol 90 (1) ◽  
pp. 015118 ◽  
Author(s):  
Hao Zeng ◽  
Peng Ye ◽  
Wentao Wei ◽  
Lianping Guo ◽  
Huiqing Pan ◽  
...  
Keyword(s):  
Real Time ◽  
High Speed ◽  
Calibration Method ◽  
Acquisition System ◽  
Adaptive Calibration ◽  
Self Adaptive

A real-time calibration method for the systematic errors of a star sensor and gyroscope units based on the payload multiplexed

Optik ◽  
2021 ◽  
Vol 225 ◽  
pp. 165731
Author(s):  
Zhongguang Yang ◽  
Xiaocheng Zhu ◽  
Zhiming Cai ◽  
Wen Chen ◽  
Jinpei Yu
Keyword(s):  
Real Time ◽  
Calibration Method ◽  
Systematic Errors ◽  
Star Sensor ◽  
Time Calibration

scholarly journals Fluorescence calibration method for single-particle aerosol fluorescence instruments

2017 ◽  
Vol 10 (5) ◽  
pp. 1755-1768 ◽  
Author(s):  
Ellis Shipley Robinson ◽  
Ru-Shan Gao ◽  
Joshua P. Schwarz ◽  
David W. Fahey ◽  
Anne E. Perring
Keyword(s):  
Real Time ◽  
Ammonium Sulfate ◽  
Fluorescence Detection ◽  
Single Particle ◽  
Calibration Method ◽  
Particle Mass ◽  
The Other ◽  
Limits Of Detection ◽  
The Relationship ◽  
Measurement Campaigns

Abstract. Real-time, single-particle fluorescence instruments used to detect atmospheric bioaerosol particles are increasingly common, yet no standard fluorescence calibration method exists for this technique. This gap limits the utility of these instruments as quantitative tools and complicates comparisons between different measurement campaigns. To address this need, we have developed a method to produce size-selected particles with a known mass of fluorophore, which we use to calibrate the fluorescence detection of a Wideband Integrated Bioaerosol Sensor (WIBS-4A). We use mixed tryptophan–ammonium sulfate particles to calibrate one detector (FL1; excitation  =  280 nm, emission  =  310–400 nm) and pure quinine particles to calibrate the other (FL2; excitation  =  280 nm, emission  =  420–650 nm). The relationship between fluorescence and mass for the mixed tryptophan–ammonium sulfate particles is linear, while that for the pure quinine particles is nonlinear, likely indicating that not all of the quinine mass contributes to the observed fluorescence. Nonetheless, both materials produce a repeatable response between observed fluorescence and particle mass. This procedure allows users to set the detector gains to achieve a known absolute response, calculate the limits of detection for a given instrument, improve the repeatability of the instrumental setup, and facilitate intercomparisons between different instruments. We recommend calibration of single-particle fluorescence instruments using these methods.

Low-Cost Air Quality Sensor Network in Munich

2020 ◽  
Author(s):  
Daniel Zollitsch ◽  
Jia Chen ◽  
Florian Dietrich ◽  
Benno Voggenreiter ◽  
Luca Setili ◽  
...  
Keyword(s):  
Air Quality ◽  
Real Time ◽  
Air Pollutants ◽  
Low Cost ◽  
Environmental Parameters ◽  
Calibration Method ◽  
Sensitivity Function ◽  
Machine Learning Algorithms ◽  
Urban Air ◽  
Monitoring Networks

<p>As the number of official monitoring stations for measuring urban air pollutants such as nitrogen oxides (NOx), particulate matter (PM) or ozone (O<sub>3</sub>) in most cities is quite small, it is difficult to determine the real human exposure to those pollutants. Therefore, several groups have established spatially higher resolved monitoring networks using low-cost sensors to create a finer concentration map [1-3].</p><p>We are currently establishing a low-cost, but high-accuracy network in Munich to measure the concentrations of NOx, PM, O<sub>3</sub>, CO and additional environmental parameters. For that, we developed a compact stand-alone sensor systems that requires low power, automatically measures the respective parameters every minute and sends the data to our server. There the raw data is transferred into concentration values by applying the respective sensitivity function for each sensor. These functions are determined by calibration measurements prior to the distribution of the sensors.</p><p>In contrast to the other existing networks, we will apply a recurring calibration method using a mobile high precision calibration unit (reference sensor) and machine learning algorithms. The results will be used to update the sensitivity function of each single sensor twice a week.  With the help of this approach, we will be able to create a calibrated real-time concentration map of air pollutants in Munich.</p><p>[1] Bigi et al.: Performance of NO, NO<sub>2</sub> low cost sensors and three calibration approaches within a real world application, Atmos. Meas. Tech., 11, 3717–3735, 2018</p><p>[2] Popoola et al., “Use of networks of low cost air quality sensors to quantify air quality in urban settings,” Atmos. Environ., 194, 58–70, 2018</p><p>[3] Schneider et al.: Mapping urban air quality in near real-time using observations from low-cost sensors and model information, Environ. Int., 106, 234–247, 2017</p>

Sign in / Sign up

Export Citation Format

Share Document