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23rd International Radar Symposium (IRS)

作者： Dominic, Hima Kromer, Mathias Echle, Reinhard Harter, Marlene Offenburg Univ Inst Unmanned Aerial Syst High Frequency Technol & EMC Lab Badstr 24 Offenburg Germany

ISBN: (纸本)9788395602054

In this study, various imaging algorithms for the localization of objects have been investigated. Therefore, an UltraWideband (UWB) radar based experimental setup with a circular antenna array is designed as part of this work. This concept could be particularly useful in microwave medical imaging applications. In order to validate its applicability in microwave imaging, different imaging algorithms have been evaluated and compared by means of our experimental setup. Accurate imaging results have been achieved with our system under multiple test-scenarios.

关键词： UWB radars imaging algorithms medical imaging scattering measurements catheter ablation

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Advancing microwave imaging algorithms and techniques

Advancing microwave imaging algorithms and techniques

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作者： Bayat, Nozhan University of Manitoba

学位级别：博士

Thisdissertation studies and develops novel techniques and algorithms in the area of mi- crowave imaging (MWI). In MWI, the objective is to create a (quantitative) image of the dielectric profile of the object of interest (OI) in a non-destructive fashion. To this end, the OI is interrogated using non-ionizing and relatively low-power microwaves which are gen- erated by some antennas. These incident microwaves will then interact with the OI, and consequently scattered electromagnetic fields will arise which contain information about the OI. These scattered fields will be collected, and then processed to extract their information so as to create the final image. This process is often referred to as the inversion of the scattered field data to reconstruct the OI's dielectric profile. Currently, MWI faces some challenges that limit its capability to become a widely-accepted imaging tool. Three of these challenges are: (i) lack of fundamental understanding about the relation between the measured scattered fields and the achievable image accuracy and resolu- tion, (ii) insufficient image accuracy and resolution for some applications, and (iii) difficulty to collect sufficient measured data due to various practical limitations. The main focus of this dissertation is to investigate and develop techniques and algorithms in an attempt to address these three challenges. This dissertation begins by introducing the concept of 'best' possible reconstruction from given MWI configurations. This concept is important since if the best possible reconstruc- tion fails to provide the features of interest, the actual blind reconstruction will not be able to provide these features either. To improve the achievable reconstruction, one option is to in- ject prior information into the algorithm. To this end, a fully automated inversion algorithm is presented that is able to incorporate prior spatial (structural) information about the OI. The proposed algorithm, which is capable of working w

关键词： Microwave imaging Microwave tomography imaging algorithms

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Implementation and Comparison of imaging Methods for Ground Penetrating Radar

Implementation and Comparison of Imaging Methods for Ground ...

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International Radar Symposium (IRS)

作者： Kromer, Mathias Aliabadi, Reza Arthur, Philip Harter, Marlene Offenburg Univ Inst Unmanned Aerial Syst Offenburg Germany

ISBN: (纸本)9798350371109;9788395602092

This work presents the comparison of the commonly used B-scan imaging method with a delay and sum (DAS) beamforming algorithm for ground penetrating radar (GPR). Utilizing an implemented ultra-wideband (UWB) stepped frequency GPR, using only in-phase data, real-world measurements are compared and discussed. The reduced complexity of the proposed system could increase the speed of data acquisition and processing as well as reduce system cost while providing similar measurement accuracy. This could be of interest for applications such as the localization of underground utility piping, archaeology or mine detection.

关键词： ground penetrating radar stepped frequency delay and sum beamforming imaging algorithms ultra-wideband radar

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Simplified Matrix Focusing imaging Algorithm for Ultrasonic Nondestructive Testing

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Chinese Journal of Mechanical Engineering 2022年第2期35卷 201-209页

作者： Xinyu Zhao Zemin Ma Jiaying Zhang School of Materials Science and Engineering Dalian Jiaotong UniversityDalian 116028China

Full matrix focusing method of ultrasonic phased array has been proved with advantages of good signal-to-noise ratio and imaging resolution in the field of Ultrasonic ***,it is still suffering from the time-consuming data acquisition and *** order to solve the problem,two simplified matrix focusing methods are provided in the *** provided method is a triangular matrix focusing algorithm based on the principle of reciprocity for the multi-channel ultrasonic *** other provided method is a trapezoidal matrix focusing algorithm based on the energy weight of the different channel to the focusing *** of data acquisition and computational is decreased with the provided simplified matrix focusing *** order to prove the validity of two provided algorithms,both side-drilled holes and oblique cracks are used for imaging *** experimental results show that the imaging quality of the triangular matrix focusing algorithm is basically consistent to that of the full matrix focusing *** imaging quality of the trapezoidal matrix focusing algorithm is slightly reduced with the amount of multi-channel data *** data acquisition and computational efficiency using the triangular matrix focusing algorithm and the trapezoidal matrix focusing algorithm have been improved significantly compared with original full matrix focusing method.

关键词： Ultrasonic NDT Phased array Full matrix focusing imaging algorithms

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A receiver-optimized total focusing method for detectability enhancement of small defects in coarse grained materials

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NDT & E INTERNATIONAL 2023年第1期140卷

作者： Ye, Tao Zhang, Jie Du, Yu Xu, Jianfeng Bai, Long Huazhong Univ Sci & Technol Sch Mech Sci & Engn State Key Lab Intelligent Mfg Equipment & Technol Wuhan 430074 Peoples R China Univ Bristol Dept Mech Engn Queens BldgUniv Walk Bristol BS81TR England

The identification and localization of small defects are among the main objectives of ultrasonic non-destructive testing (NDT). In particular, the inspection of polycrystalline materials remains a challenge due to ultrasonic attenuation and backscatter noise caused by grain scattering. An adaptive ultrasonic array imaging algorithm is proposed in this paper, which is capable of enhancing the signal-to-noise ratio (SNR) of small subwavelength defects. The proposed approach adopts an iterative optimization procedure based on sequential backward selection, and is termed receiver optimized total focusing method (ROTFM). ROTFM is formulated in a baseline subtraction (BS) setting, and it is shown to achieve higher defect SNRs compared to TFM results obtained by directly applying the BS method to measured array data. More importantly, the performance of the proposed ROTFM is robust to time and spatial misalignments, and hence, it alleviates the need for complex compensation schemes when performing imaging computations. Compared to conventional TFM, ROTFM achieved an average SNR improvement of 3.41 dB and 6.05 dB in experiments for four test defects (cracks and holes of sizes 0.5 mm and 1 mm) at the frequencies of 5 MHz and 7 MHz, respectively.

关键词： Defect detection TFM Polycrystalline materials imaging algorithms

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Enhancing damage localisation in critical areas of storage tanks in floating production storage and offloadings with a guided wave structural health monitoring system

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STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL 2023年第2期22卷 993-1007页

作者： Dambros Menin, Paulo de Abreu Correa, Lucio Rosauro Clarke, Thomas Gabriel Alvin Liang, Denis Fed Univ Rio Grande Sul UFRGS Min Met & Mat Engn PPGEM Av Bento Goncalves 9500 BR-90650001 Porto Alegre RS Brazil Res & Dev Ctr CENPES Rio De Janeiro Brazil

A guided wave monitoring system for storage tanks of floating production storage and offloading units was tested on a panel which is representative of a critical region of such structures. Initially, baseline signals of the undamaged structure were acquired within a representative temperature range. These signals were then processed with the optimal baseline subtraction, optimal stretch and phase-shift compensation algorithms. Two distinct damage indexes were generated from the residual signals in order to verify the detection capability of the system. A delay-and-sum image algorithm was then applied to the residual signals in order to evaluate the defect localisation capabilities of the system. These images were than post-processed with three different methods, one based on a probabilistic approach, another on singular value decomposition and also with a combination of these two methods. The signal-to-noise ratio (SNR) gain obtained by applying the post-processing strategies was calculated and compared to the original images. Results demonstrate that the system is capable of detecting localised wall loss and indicating its correct position for damage larger than 20% wall thickness loss. Results also show that the post-processing methods helped to improve the SNR, leading to gains of more than 15dB in damage to artefact amplitude ratios.

关键词： floating production storage and offloading structural health monitoring guided waves imaging algorithms

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Accuracy of artificial intelligence software for the detection of confirmed pleural effusion in thoracic radiographs in dogs

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VETERINARY RADIOLOGY & ULTRASOUND 2022年第5期63卷 573-579页

作者： Muller, Thiago Rinaldi Solano, Mauricio Tsunemi, Mirian Harumi Tufts Univ Dept Clin Sci Cummings Sch Vet Med North Grafton MA USA Sao Paulo State Univ Dept Biostat Sao Paulo Brazil

The use of artificial intelligence (AI) algorithms in diagnostic radiology is a developing area in veterinary medicine and may provide substantial benefit in many clinical settings. These range from timely image interpretation in the emergency setting when no boarded radiologist is available to allowing boarded radiologists to focus on more challenging cases that require complex medical decision making. Testing the performance of artificial intelligence (AI) software in veterinary medicine is at its early stages, and only a scant number of reports of validation of AI software have been published. The purpose of this study was to investigate the performance of an AI algorithm (Vetology AI (R)) in the detection of pleural effusion in thoracic radiographs of dogs. In this retrospective, diagnostic case-controlled study, 62 canine patients were recruited. A control group of 21 dogs with normal thoracic radiographs and a sample group of 41 dogs with confirmed pleural effusion were selected from the electronic medical records at the Cummings School of Veterinary Medicine. The images were cropped to include only the area of interest (i.e., thorax). The software then classified images into those with pleural effusion and those without. The AI algorithm was able to determine the presence of pleural effusion with 88.7% accuracy (P < 0.05). The sensitivity and specificity were 90.2% and 81.8%, respectively (positive predictive value, 92.5%;negative predictive value, 81.8%). The application of this technology in the diagnostic interpretation of thoracic radiographs in veterinary medicine appears to be of value and warrants further investigation and testing.

关键词： imaging algorithms machine learning convolutional neural network pleural effusion thorax radiograph dog canine X-ray

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Design of a Semi-Circular Finger Shaped Antenna with Metamaterial Loaded Ground for Brain Tumor Detection and Localization

Design of a Semi-Circular Finger Shaped Antenna with Metamat...

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2023 IEEE Microwaves, Antennas, and Propagation Conference, MAPCON 2023

作者： Lone, Jehangir Hameed Rasool, Umhara Sheikh, Javaid A. Balkhi, Altaf A. University of Kashmir P.G Electronics and It Srinagar India Basic Engineering and Applied Sciences College of Agriculture Engineering & Technology SKAUST-K Srinagar Shalimar India

ISBN: (纸本)9798350328264

In this communication, an innovative finger shaped antenna with unidirectional radiation pattern resonating at 2.8 GHz in free space and having an operational bandwidth of 0.6 GHz for Tumor detection and localization system is proposed. The reported design has minimal footprint area of 28× 28× 0.75 mm3 and showcases the remarkable results. The prospective antenna is designed on a Rogers TMM 4 substrate with the relative permittivity of 4.5 and utilizes a partial ground plane measuring 6 mm in length to expand the bandwidth and achieve the desired operational frequency. The humanoid head phantom comprising of 6 layers (brain, CSF, dura, skull, fat and skin) and the tumor, which possesses various physical and electromagnetic characteristics is designed within the HFSS. The detection of tumor in brain is done by analyzing the difference in scattering parameters for healthy and diseased tissue. However, the localization and sizing of the tumor is done by extracting the phase and magnitude of the electric field rather than utilizing complex imaging algorithms saving critical resources. Furthermore, the antenna's Specific Absorption Rate (SAR) for a regular head phantom and a phantom with a tumor is measured at 0.16779 W/Kg and 0.206 W/kg correspondingly, while these values are lesser than the average SAR of 2 W/kg. © 2023 IEEE.

关键词： imaging algorithms localization Operational bandwidth

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Assessing Patient-Specific Microwave Breast imaging in Clinical Case Studies

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SENSORS 2021年第23期21卷 8048-8048页

作者： O'Loughlin, Declan Elahi, Muhammad Adnan Lavoie, Benjamin R. Fear, Elise C. O'Halloran, Martin Trinity Coll Dublin Elect & Elect Engn Dublin D02 PN40 Ireland Natl Univ Ireland Galway Elect & Elect Engn Galway H91 TK33 Ireland Univ Calgary Elect & Comp Engn Calgary AB T2N 1N4 Canada

Microwave breast imaging has seen increasing use in clinical investigations in the past decade with over eight systems having being trialled with patients. The majority of systems use radar-based algorithms to reconstruct the image shown to the clinician which requires an estimate of the dielectric properties of the breast to synthetically focus signals to reconstruct the image. Both simulated and experimental studies have shown that, even in simplified scenarios, misestimation of the dielectric properties can impair both the image quality and tumour detection. Many methods have been proposed to address the issue of the estimation of dielectric properties, but few have been tested with patient images. In this work, a leading approach for dielectric properties estimation based on the computation of many candidate images for microwave breast imaging is analysed with patient images for the first time. Using five clinical case studies of both healthy breasts and breasts with abnormalities, the advantages and disadvantages of computational patient-specific microwave breast image reconstruction are highlighted.

关键词： microwave breast imaging imaging algorithms patient images patient-specific imaging

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Muon tomography imaging algorithms for nuclear threat detection inside large volume containers with the Muon Portal detector

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NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2013年 728卷 59-68页

作者： Riggi, S. Antonuccio-Delogu, V. Bandieramonte, M. Becciani, U. Costa, A. La Rocca, P. Massimino, P. Petta, C. Pistagna, C. Riggi, F. Sciacca, E. Vitello, F. INAF Osservatorio Astrofis Catania Catania Italy Univ Catania Dip Fis & Astron I-95124 Catania Italy INFN Sect Catania Catania Italy

Muon tomographic visualization techniques try to reconstruct a 3D image as close as possible to the real localization of the objects being probed. Statistical algorithms under test for the reconstruction of muon tomographic images in the Muon Portal Project are discussed here. Autocorrelation analysis and clustering algorithms have been employed within the context of methods based on the Point Of Closest Approach (POCA) reconstruction tool. An iterative method based on the log-likelihood approach was also implemented. Relative merits of all such methods are discussed, with reference to full GEANT4 simulations of different scenarios, incorporating medium and high-Z objects inside a container. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Muon tomography imaging algorithms Clustering methods Autocorrelation analysis Maximum likelihood EM algorithm

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