An Autofocus Algorithm Considering Wavelength Changes for Large Scale Microscopic Hyperspectral Pathological Imaging System

2022 ◽  
Author(s):  
Qing Zhang ◽  
Yan Wang ◽  
Qingli Li ◽  
Xiang Tao ◽  
Xiufeng Zhou ◽  
...  
Keyword(s):  
Large Scale ◽  
Imaging System ◽  
Autofocus Algorithm

scholarly journals Rapid Single Image-Based DTM Estimation from ExoMars TGO CaSSIS Images Using Generative Adversarial U-Nets

2021 ◽  
Vol 13 (15) ◽  
pp. 2877
Author(s):  
Yu Tao ◽  
Siting Xiong ◽  
Susan J. Conway ◽  
Jan-Peter Muller ◽  
Anthony Guimpier ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Imaging System ◽  
Landing Site ◽  
Parameter Tuning ◽  
Processing Parameters ◽  
Input Image ◽  
Large Area ◽  
Laser Altimeter ◽  
Imaging Science

The lack of adequate stereo coverage and where available, lengthy processing time, various artefacts, and unsatisfactory quality and complexity of automating the selection of the best set of processing parameters, have long been big barriers for large-area planetary 3D mapping. In this paper, we propose a deep learning-based solution, called MADNet (Multi-scale generative Adversarial u-net with Dense convolutional and up-projection blocks), that avoids or resolves all of the above issues. We demonstrate the wide applicability of this technique with the ExoMars Trace Gas Orbiter Colour and Stereo Surface Imaging System (CaSSIS) 4.6 m/pixel images on Mars. Only a single input image and a coarse global 3D reference are required, without knowing any camera models or imaging parameters, to produce high-quality and high-resolution full-strip Digital Terrain Models (DTMs) in a few seconds. In this paper, we discuss technical details of the MADNet system and provide detailed comparisons and assessments of the results. The resultant MADNet 8 m/pixel CaSSIS DTMs are qualitatively very similar to the 1 m/pixel HiRISE DTMs. The resultant MADNet CaSSIS DTMs display excellent agreement with nested Mars Reconnaissance Orbiter Context Camera (CTX), Mars Express’s High-Resolution Stereo Camera (HRSC), and Mars Orbiter Laser Altimeter (MOLA) DTMs at large-scale, and meanwhile, show fairly good correlation with the High-Resolution Imaging Science Experiment (HiRISE) DTMs for fine-scale details. In addition, we show how MADNet outperforms traditional photogrammetric methods, both on speed and quality, for other datasets like HRSC, CTX, and HiRISE, without any parameter tuning or re-training of the model. We demonstrate the results for Oxia Planum (the landing site of the European Space Agency’s Rosalind Franklin ExoMars rover 2023) and a couple of sites of high scientific interest.

scholarly journals Microwave Tomography System for Methodical Testing of Human Brain Stroke Detection Approaches

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Ilja Merunka ◽  
Andrea Massa ◽  
David Vrba ◽  
Ondrej Fiser ◽  
Marco Salucci ◽  
...  
Keyword(s):  
Human Brain ◽  
Antenna Array ◽  
Large Scale ◽  
Imaging System ◽  
Reconstruction Algorithm ◽  
Human Head ◽  
Repeated Measurements ◽  
Measuring System ◽  
Dielectric Parameters ◽  
Iterative Reconstruction Algorithm

In this work, a prototype of a laboratory microwave imaging system suitable to methodically test the ability to image, detect, and classify human brain strokes using microwave technology is presented. It consists of an antenna array holder equipped with ten newly developed slot bowtie antennas, a 2.5 D reconfigurable and replaceable human head phantom, stroke phantoms, and related measuring technology and software. This prototype was designed to allow measurement of a complete S-matrix of the antenna array. The reconfigurable and replaceable phantom has currently 23 different predefined positions for stroke phantom placement. This setting allows repeated measurements for the stroke phantoms of different types, sizes/shapes, and at different positions. It is therefore suitable for large-scale measurements with high variability of measured data for stroke detection and classification based on machine learning methods. In order to verify the functionality of the measuring system, S-parameters were measured for a hemorrhagic phantom sequentially placed on 23 different positions and distributions of dielectric parameters were reconstructed using the Gauss-Newton iterative reconstruction algorithm. The results correlate well with the actual position of the stroke phantom and its type.

scholarly journals “Two-Cell Assemblage” Assay: A Simple in vitro Method for Screening Hair Growth-Promoting Compounds

2020 ◽  
Vol 8 ◽  
Author(s):  
Sunhyae Jang ◽  
Jungyoon Ohn ◽  
Bo Mi Kang ◽  
Minji Park ◽  
Kyu Han Kim ◽  
...  
Keyword(s):  
Stem Cell ◽  
Hair Growth ◽  
Large Scale ◽  
Cell Activation ◽  
Imaging System ◽  
Control Group ◽  
Dependent Manner ◽  
Growth Promoting ◽  
Axis Length

Alopecia arises due to inadequate hair follicle (HF) stem cell activation or proliferation, resulting in prolongation of the telogen phase of the hair cycle. Increasing therapeutic and cosmetic demand for alleviating alopecia has driven research toward the discovery or synthesis of novel compounds that can promote hair growth by inducing HF stem cell activation or proliferation and initiating the anagen phase. Although several methods for evaluating the hair growth-promoting effects of candidate compounds are being used, most of these methods are difficult to use for large scale simultaneous screening of various compounds. Herein, we introduce a simple and reliable in vitro assay for the simultaneous screening of the hair growth-promoting effects of candidate compounds on a large scale. In this study, we first established a 3D co-culture system of human dermal papilla (hDP) cells and human outer root sheath (hORS) cells in an ultra-low attachment 96-well plate, where the two cell types constituted a polar elongated structure, named “two-cell assemblage (TCA).” We observed that the long axis length of the TCA gradually increased for 5 days, maintaining biological functional integrity as reflected by the increased expression levels of hair growth-associated genes after treatment with hair growth-promoting molecules. Interestingly, the elongation of the TCA was more prominent following treatment with the hair growth-promoting molecules (which occurred in a dose-dependent manner), compared to the control group (p < 0.05). Accordingly, we set the long axis length of the TCA as an endpoint of this assay, using a micro confocal high-content imaging system to measure the length, which can provide reproducible and reliable results in an adequate timescale. The advantages of this assay are: (i) it is physiologically and practically advantageous as it uses 3D cultured two-type human cells which are easily available; (ii) it is simple as it uses length as the only endpoint; and (iii) it is a high throughput system, which screens various compounds simultaneously. In conclusion, the “TCA” assay could serve as an easy and reliable method to validate the hair growth-promoting effect of a large volume of library molecules.

STANDOFF SENSING AND IMAGING OF EXPLOSIVE RELATED CHEMICAL AND BIO-CHEMICAL MATERIALS USING THz-TDS

2007 ◽  
Vol 17 (02) ◽  
pp. 239-249 ◽  
Author(s):  
Hua Zhong ◽  
Albert Redo-Sanchez ◽  
Xi-Cheng Zhang
Keyword(s):  
Remote Sensing ◽  
Glutamic Acid ◽  
Time Domain ◽  
Large Scale ◽  
Imaging System ◽  
Terahertz Time Domain Spectroscopy ◽  
Multiple Absorption ◽  
Thz Absorption ◽  
Absorption Features ◽  
Chemical Materials

We report the sensing and imaging of explosive related chemical and bio-chemical materials by using terahertz time domain spectroscopy (THz-TDS) at standoff distance. The 0.82 THz absorption peak of RDX is observed at a distance up to 30 m away from the emitter and receiver. Multiple absorption features of RDX, 2,4-DNT and Glutamic Acid are identified by using a large scale 2-D imaging system. These results support the feasibility of using THz-TDS technique in remote sensing and detection of chemical materials.

Large-scale scene real-time infrared simulation based on texture blending

2016 ◽  
Vol 9 (4) ◽  
pp. 406-415
Author(s):  
Yuye Wang ◽  
Guofeng Zhang ◽  
Xiaoguang Hu
Keyword(s):  
Large Scale ◽  
Infrared Imaging ◽  
Imaging System ◽  
Infrared Image ◽  
Frame Rate ◽  
Theoretical Research ◽  
Content Type ◽  
High Frame Rate ◽  
Specific Target ◽  
Infrared Imaging System

Purpose Infrared simulation plays an important role in small and affordable unmanned aerial vehicles. Its key and main goal is to get the infrared image of a specific target. Infrared physical model is established through a theoretical research, thus the temperature field is available. Then infrared image of a specific target can be simulated properly while taking atmosphere state and effect of infrared imaging system into account. For recent years, some research has been done in this field. Among them, the infrared simulation for large scale is still a key problem to be solved. In this passage, a method of classification based on texture blending is proposed and this method effectively solves the problem of classification of large number of images and increase the frame rate of large infrared scene rendering. The paper aims to discuss these issues. Design/methodology/approach Mosart Atmospheric Tool (MAT) is used first to calculate data of sun radiance, skyshine radiance, path radiance, temperatures of different material which is an offline process. Then, shader in OGRE does final calculation to get simulation result and keeps a high frame rate. Considering this, the authors convert data in MAT file into textures which can be easily handled by shader. In shader responding, radiance can be indexed by information of material, vertex normal, eye and sun. Adding the effect of infrared imaging system, the final radiance distribution is obtained. At last, the authors get infrared scene by converting radiance to grayscale. Findings In the fragment shader, fake infrared textures are used to look up temperature which can calculate radiance of itself and related radiance. Research limitations/implications The radiance is transferred into grayscale image while considering effect of infrared imaging system. Originality/value Simulation results show that a high frame rate can be reached while guaranteeing the fidelity.

scholarly journals QuickStitch for seamless stitching of confocal mosaics through high-pass filtering and recursive normalization

2016 ◽  
Author(s):  
Pavel A. Brodskiy ◽  
Paulina M. Eberts ◽  
Cody Narciso ◽  
Jochen Kursawe ◽  
Alexander Fletcher ◽  
...  
Keyword(s):  
Open Source ◽  
Large Scale ◽  
Imaging System ◽  
Tissue Level ◽  
Cellular Level ◽  
Specific Information ◽  
Open Source Tool ◽  
The Individual ◽  
User Friendly ◽  
High Pass

ABSTRACTFluorescence micrographs naturally exhibit darkening around their edges (vignetting), which makes seamless stitching challenging. If vignetting is not corrected for, a stitched image will have visible seams where the individual images (tiles) overlap, introducing a systematic error into any quantitative analysis of the image. Although multiple vignetting correction methods exist, there remains no open-source tool that robustly handles large 2D immunofluorescence-based mosaic images. Here, we develop and validate QuickStitch, a tool that applies a recursive normalization algorithm to stitch large-scale immunofluorescence-based mosaics without incurring vignetting seams. We demonstrate how the tool works successfully for tissues of differing size, morphology, and fluorescence intensity. QuickStitch requires no specific information about the imaging system. It is provided as an open-source tool that is both user friendly and extensible, allowing straightforward incorporation into existing image processing pipelines. This enables studies that require accurate segmentation and analysis of high-resolution datasets when parameters of interest include both cellular-level phenomena and larger tissue-level regions of interest.

scholarly journals A Modular Microarray Imaging System for Highly Specific COVID-19 Antibody Testing

2020 ◽  
Author(s):  
Per Niklas Hedde ◽  
Timothy J. Abram ◽  
Aarti Jain ◽  
Rie Nakajima ◽  
Rafael Ramiro de Assis ◽  
...  
Keyword(s):  
Large Scale ◽  
Imaging System ◽  
Turnaround Time ◽  
Mitigation Measures ◽  
Antibody Testing ◽  
Imaging Device ◽  
Highly Sensitive ◽  
Finger Prick ◽  
Specific Manner ◽  
To Come

AbstractTo detect the presence of antibodies in blood against SARS-CoV-2 in a highly sensitive and specific manner, here we describe a robust, inexpensive ($200), 3D-printable portable imaging platform (TinyArray imager) that can be deployed immediately in areas with minimal infrastructure to read coronavirus antigen microarrays (CoVAMs) that contain a panel of antigens from SARS-CoV-2, SARS-1, MERS, and other respiratory viruses. Application includes basic laboratories and makeshift field clinics where a few drops of blood from a finger prick could be rapidly tested in parallel for the presence of antibodies to SARS-CoV-2 with a test turnaround time of only 2-4 h. To evaluate our imaging device, we probed and imaged coronavirus microarrays with COVID-19-positive and negative sera and achieved a performance on par with a commercial microarray reader 100x more expensive than our imaging device. This work will enable large scale serosurveillance, which can play an important role in the months and years to come to implement efficient containment and mitigation measures, as well as help develop therapeutics and vaccines to treat and prevent the spread of COVID-19.

scholarly journals A MODIFIED PROJECTIVE TRANSFORMATION SCHEME FOR MOSAICKING MULTI-CAMERA IMAGING SYSTEM EQUIPPED ON A LARGE PAYLOAD FIXED-WING UAS

2015 ◽  
Vol XL-3/W2 ◽  
pp. 87-93 ◽  
Author(s):  
J. P. Jhan ◽  
Y. T. Li ◽  
J. Y. Rau
Keyword(s):  
Large Scale ◽  
Imaging System ◽  
Collection Efficiency ◽  
Projective Transformation ◽  
Operation Time ◽  
Bundle Adjustment ◽  
Aerial Images ◽  
Mountainous Area ◽  
Topographic Map ◽  
Camera System

In recent years, Unmanned Aerial System (UAS) has been applied to collect aerial images for mapping, disaster investigation, vegetation monitoring and etc. It is a higher mobility and lower risk platform for human operation, but the low payload and short operation time reduce the image collection efficiency. In this study, one nadir and four oblique consumer grade DSLR cameras composed multiple camera system is equipped on a large payload UAS, which is designed to collect large ground coverage images in an effective way. The field of view (FOV) is increased to 127 degree, which is thus suitable to collect disaster images in mountainous area. The synthetic acquired five images are registered and mosaicked as larger format virtual image for reducing the number of images, post processing time, and for easier stereo plotting. Instead of traditional image matching and applying bundle adjustment method to estimate transformation parameters, the IOPs and ROPs of multiple cameras are calibrated and derived the coefficients of modified projective transformation (MPT) model for image mosaicking. However, there are some uncertainty of indoor calibrated IOPs and ROPs since the different environment conditions as well as the vibration of UAS, which will cause misregistration effect of initial MPT results. Remaining residuals are analysed through tie points matching on overlapping area of initial MPT results, in which displacement and scale difference are introduced and corrected to modify the ROPs and IOPs for finer registration results. In this experiment, the internal accuracy of mosaic image is better than 0.5 pixels after correcting the systematic errors. Comparison between separate cameras and mosaic images through rigorous aerial triangulation are conducted, in which the RMSE of 5 control and 9 check points is less than 5 cm and 10 cm in planimetric and vertical directions, respectively, for all cases. It proves that the designed imaging system and the proposed scheme have potential to create large scale topographic map.

Combined Transducer and Nonlinear Tissue Propagation Simulations

1999 ◽  
Author(s):  
Gregory L. Wojcik ◽  
John C. Mould ◽  
Laura M. Carcione
Keyword(s):  
Cross Sections ◽  
Large Scale ◽  
Imaging System ◽  
Second Harmonic ◽  
Order Approximation ◽  
Acoustic Power ◽  
Acoustic Medium ◽  
Power Indices ◽  
Design Qualification ◽  
Response Modes

Abstract Ultrasonic imaging system evaluation is often based on models of the transducer as a distribution of baffled piston sources, and of the tissue as a homogeneous, linear acoustic medium, e.g., Jensen’s Field code. In reality, these are fairly gross idealizations, since the transducer exhibits more complicated response modes and real tissue is inhomogeneous and nonlinear. Greater model fidelity would be useful, especially in the context of transducer design qualification, second harmonic imaging, and acoustic power indices. To this end we combine 2D finite element models of transducer dynamics with highly accurate 2D finite difference propagation models in the large-scale inhomogeneous tissue cross-sections. Transducer models employ the time-domain code, PZFlex, and tissue models utilize a new pseudospectral solver to be included in PZFlex. The pseudospectral algorithm solves the inhomogeneous acoustic wave equation using FFTs for high order approximation of the spatial differential operator and a fourth-order, explicit time integrator. Second-order (B/A) nonlinearity and frequency-accurate, causal absorption are included. We describe the algorithmic and modeling issues, and present a suite of simulations in lossy, nonlinear abdominal cross sections and tissue showing coupling of the 1D medical array to the tissue model and scattering from deeper inhomogeneities and back to the transducer. In contrast to paraxial schemes, like the KZK method, details of the field transmitted from the transducer and all backscatter within the model are included. However, models are currently limited to 2D (plane or axisymmetric) on readily available hardware.

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