OPTIMIZATION OF DESIGN PARAMETERS FOR FLUORESCENCE LAMINAR OPTICAL TOMOGRAPHY

2011 ◽  
Vol 04 (03) ◽  
pp. 309-323 ◽  
Author(s):  
CHAO-WEI CHEN ◽  
YU CHEN
Keyword(s):  
Imaging Technique ◽  
Optical Tomography ◽  
Design Parameters ◽  
Optimization Strategy ◽  
Scattering Medium ◽  
Value Analysis ◽  
Molecular Information ◽  
Depth Sensitivity ◽  
Detector Configurations ◽  
Imaging Performance

Laminar optical tomography (LOT) is a mesoscopic tomographic imaging technique ranging between confocal microscopy and diffuse optical tomography (DOT). Fluorescence LOT (FLOT) provides depth-resolved molecular information with 100–200 μm resolution over 2–3 mm depth. In this study, we use Monte Carlo simulation and singular-value analysis (SVA) to optimize the source-detector configurations for potential enhancement of FLOT imaging performance. The effects of different design parameters, including source incidence and detector collection angles, detector number, and sampling density, are presented. The results indicate that angled incidence/detection configuration might improve the imaging resolution and depth sensitivity, especially for low-scattering medium. Increasing the number of detectors and the number of scanning steps will also result in enhanced imaging performance. We also demonstrate that the optimal imaging performance depends upon the background scattering coefficient. Our result might provide an optimization strategy for FLOT or LOT experimental setup.

scholarly journals Modeling Combined Ultrasound and Photoacoustic Imaging: Simulations aiding Device Development and Deep Learning

2020 ◽  
Author(s):  
Sumit Agrawal ◽  
Ajay Dangi ◽  
Sri-Rajasekhar Kothapalli
Keyword(s):  
Deep Learning ◽  
Photoacoustic Imaging ◽  
Design Parameters ◽  
Simulation Platform ◽  
Detector Arrays ◽  
Device Development ◽  
Effective Implementation ◽  
Optical Attenuation ◽  
Molecular Information ◽  
Imaging Performance

AbstractCombined ultrasound and photoacoustic (USPA) imaging has attracted several clinical applications due to its ability to simultaneously display structural and molecular information of deep biological tissue in real time. However, the depth dependent optical attenuation and the unknown optical and acoustic heterogeneities, limit the USPA imaging performance, especially from deeper tissue regions. Novel instrumentation, image reconstruction and deep learning methods are currently being explored to improve the USPA image quality. Effective implementation of these approaches requires a reliable USPA simulation tool capable of generating US based anatomical and PA based molecular information. Here, we developed a hybrid USPA simulation platform by integrating finite element models of light and ultrasound propagation. The feasibility of modeling US combined with optical fluence dependent multispectral PA imaging is demonstrated using in silico homogeneous and heterogeneous prostate tissue. The platform allows optimization of device design parameters, such as the aperture size and frequency of light source and ultrasound detector arrays. In addition, the potential of this simulation platform to generative massive USPA datasets aiding the data driven deep-learning enhanced USPA imaging has been validated using both simulations and experiments.

The influence of confocal microscope design on imaging performance

1993 ◽  
Vol 51 ◽  
pp. 144-145
Author(s):  
C J R Sheppard
Keyword(s):  
Image Quality ◽  
Fluorescence Imaging ◽  
Confocal Microscope ◽  
Industrial Applications ◽  
Three Dimensions ◽  
Design Parameters ◽  
Weak Signals ◽  
Size And Shape ◽  
Imaging Performance ◽  
Fundamental Limitation

The confocal microscope is now widely used in both biomedical and industrial applications for imaging, in three dimensions, objects with appreciable depth. There are now a range of different microscopes on the market, which have adopted a variety of different designs. The aim of this paper is to explore the effects on imaging performance of design parameters including the method of scanning, the type of detector, and the size and shape of the confocal aperture.It is becoming apparent that there is no such thing as an ideal confocal microscope: all systems have limitations and the best compromise depends on what the microscope is used for and how it is used. The most important compromise at present is between image quality and speed of scanning, which is particularly apparent when imaging with very weak signals. If great speed is not of importance, then the fundamental limitation for fluorescence imaging is the detection of sufficient numbers of photons before the fluorochrome bleaches.

scholarly journals Hyperspectral Three-Dimensional Fluorescence Imaging Using Snapshot Optical Tomography

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3652
Author(s):  
Cory Juntunen ◽  
Isabel M. Woller ◽  
Yongjin Sung
Keyword(s):  
Fourier Transform ◽  
3D Imaging ◽  
Optical Tomography ◽  
Three Dimensional ◽  
High Spectral Resolution ◽  
Functional Information ◽  
Fluorescent Beads ◽  
Different Depths ◽  
Projection Images ◽  
Imaging Performance

Hyperspectral three-dimensional (3D) imaging can provide both 3D structural and functional information of a specimen. The imaging throughput is typically very low due to the requirement of scanning mechanisms for different depths and wavelengths. Here we demonstrate hyperspectral 3D imaging using Snapshot projection optical tomography (SPOT) and Fourier-transform spectroscopy (FTS). SPOT allows us to instantaneously acquire the projection images corresponding to different viewing angles, while FTS allows us to perform hyperspectral imaging at high spectral resolution. Using fluorescent beads and sunflower pollens, we demonstrate the imaging performance of the developed system.

An Adjoint Based Approach for Optimal Design of Morphing SMP

2013 ◽  
Author(s):  
Shuang Wang ◽  
John C. Brigham
Keyword(s):  
Shape Change ◽  
Mechanical Energy ◽  
Optimization Methods ◽  
Design Parameters ◽  
Optimization Strategy ◽  
Thermally Activated ◽  
Gradient Based ◽  
Nonlinear Optimization Methods ◽  
Numerical Representations ◽  
Objective Functional

This work presents a strategy to identify the optimal localized activation and actuation for a morphing thermally activated SMP structure or structural component to obtain a targeted shape change or set of shape features, subject to design objectives such as minimal total required energy and time. This strategy combines numerical representations of the SMP structure’s thermo-mechanical behavior subject to activation and actuation with gradient-based nonlinear optimization methods to solve the morphing inverse problem that includes minimizing cost functions which address thermal and mechanical energy, morphing time, and damage. In particular, the optimization strategy utilizes the adjoint method to efficiently compute the gradient of the objective functional(s) with respect to the design parameters for this coupled thermo-mechanical problem.

Analysis and Optimization of a Passive Micromixer With Curved-Shaped Baffles for Efficient Mixing With Low Pressure Loss in Continuous Flow

2010 ◽  
Author(s):  
Cesar A. Cortes-Quiroz ◽  
Alireza Azarbadegan ◽  
Emadaldin Moeendarbary ◽  
Mehrdad Zangeneh
Keyword(s):  
Pressure Loss ◽  
Cost Effective ◽  
Optimization Method ◽  
Secondary Flows ◽  
Design Parameters ◽  
Mixing Efficiency ◽  
Outlet Section ◽  
Optimization Strategy ◽  
Mixing Index ◽  
Trade Offs

Numerical simulations and an optimization method are used to study the design of a planar T-micromixer with curved-shaped baffles in the mixing channel. The mixing efficiency and the pressure loss in the mixing channel have been evaluated for Reynolds number (Re) in the mixing channel in the range 1 to 250. A Mixing index (Mi) has been defined to quantify the mixing efficiency. Three geometric dimensions: radius of baffle, baffles pitch and height of the channel, are taken as design parameters, whereas the mixing index at the outlet section and the pressure loss in the mixing channel are the performance parameters used to optimize the micromixer geometry. To investigate the effect of design and operation parameters on the device performance, a systematic design and optimization methodology is applied, which combines Computational Fluid Dynamics (CFD) with an optimization strategy that integrates Design of Experiments (DOE), Surrogate modeling (SM) and Multi-Objective Genetic Algorithm (MOGA) techniques. The Pareto front of designs with the optimum trade-offs of mixing index and pressure loss is obtained for different values of Re. The micromixer can enhance mixing using the mechanisms of diffusion (lower Re) and convection (higher Re) to achieve values over 90%, in particular for Re in the order of 100 that has been found the cost-effective level for volume flow. This study applies a systematic procedure for evaluation and optimization of a planar T-mixer with baffles in the channel that promote transversal 3-D flow as well as recirculation secondary flows that enhance mixing.

scholarly journals Depth sensitivity and image reconstruction analysis of dense imaging arrays for mapping brain function with diffuse optical tomography

2009 ◽  
Vol 48 (10) ◽  
pp. D137 ◽  
Author(s):  
Hamid Dehghani ◽  
Brian R. White ◽  
Benjamin W. Zeff ◽  
Andrew Tizzard ◽  
Joseph P. Culver
Keyword(s):  
Image Reconstruction ◽  
Brain Function ◽  
Optical Tomography ◽  
Diffuse Optical Tomography ◽  
Imaging Arrays ◽  
Depth Sensitivity

Measurement of object position inside high-scattering medium by use of optical tomography method with neural processing

2003 ◽  
Author(s):  
Andrzej W. Domanski ◽  
K. Pierscinski ◽  
M. Zielinski ◽  
Miroslaw A. Karpierz ◽  
Marek W. Sierakowski ◽  
...  
Keyword(s):  
Optical Tomography ◽  
Neural Processing ◽  
Scattering Medium ◽  
Object Position ◽  
Tomography Method

Multidisciplinary 3D-Optimization of a Fan Stage Performance Map With Consideration of the Static and Dynamic Rotor Mechanics

2010 ◽  
Author(s):  
Ulrich Siller ◽  
Marcel Aulich
Keyword(s):  
Pressure Ratio ◽  
Stability Margin ◽  
Structural Mechanics ◽  
Aerodynamic Performance ◽  
Response Surfaces ◽  
Optimization Process ◽  
Design Parameters ◽  
Optimization Strategy ◽  
Rotor Aerodynamics ◽  
High Pressure Ratio

Achievement of an optimal compressor design with respect to its aerodynamic performance and feasible structural mechanics within an automated optimization process is subject of this paper. The compressor considered is a highly loaded, transonic fan stage, designed for achievement of a very high pressure ratio. To ensure operation in highly integrated installation conditions, a sufficient stability margin is of major concern. Multiple aerodynamic operating points at two rotational speeds allowed optimization of both the stability margin and the working line stage efficiency. On the part of structural mechanics, several static stress criteria were addressed for definite blade regions as well as the dynamic blade behavior in terms of the Campbell diagram. An optimization strategy was chosen, which targeted firstly on the fulfillment of multiple mechanical and aerodynamical constraints, while the aerodynamic performance was under constraint itself. Upon achievement, optimization aimed for maximum aerodynamic performance while keeping mechanics feasible. Response surfaces have been incorporated in the optimization process to reconcile costly high fidelity CFD and structural simulations with the large number of 114 free design parameters. Furthermore, optimization on these models enabled a successfully accomplishment of the constraint issue by a large number of numerically cheaper fitness evaluations. Starting from an already optimized baseline configuration, the current work targeted an improvement of the rotor aerodynamics in the transonic hub region and the resolution of previously unsolved problems concerning the rotor structural mechanics. Free design parameters were hub and casing contours in the rotor part, the shape of the leading and trailing blade edges and a high degree of freedom for rotor profile sections in the lower half of the blade.

Multiobjective Optimization Design of a Pump–Turbine Impeller Based on an Inverse Design Using a Combination Optimization Strategy

2013 ◽  
Vol 136 (1) ◽  
Author(s):  
Wei Yang ◽  
Ruofu Xiao
Keyword(s):  
Response Surface ◽  
Optimization Design ◽  
Design Method ◽  
Inverse Design ◽  
Design Parameters ◽  
Surface Model ◽  
Optimization Strategy ◽  
Pump Turbine ◽  
Combination Optimization ◽  
Final Design

This paper presents an automatic multiobjective hydrodynamic optimization strategy for pump–turbine impellers. In the strategy, the blade shape is parameterized based on the blade loading distribution using an inverse design method. An efficient response surface model relating the design parameters and the objective functions is obtained. Then, a multiobjective evolutionary algorithm is applied to the response surface functions to find a Pareto front for the final trade-off selection. The optimization strategy was used to redesign a scaled pump–turbine. Model tests were conducted to validate the final design and confirm the validity of the design strategy.

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