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Breast Tumor Detection Using Multistatic Microwave Imaging With Vivaldi Antennas Utilizing a Novel Preprocessing Stage in DAS algorithm

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2025年 74卷

作者： Asok, Athul O. Nath, S. J. Gokul Dey, Sukomal IIT Palakkad Dept Elect Engn Palakkad 678623 Kerala India

A new imaging setup with a novel preprocessing stage is proposed in this work for the detection of early stage breast tumors. A multistatic imaging setup with nine antennas is made to detect multiple tumors embedded inside the lab-made realistic homogeneous and heterogeneous breast phantoms. An ultrawideband signal is transmitted from the transmitting antipodal Vivaldi antenna (AVA), and the received signals are collected by the remaining eight antennas connected to an RF switch matrix. The received signals are serially transmitted to the PC connected to the switching matrix via the vector network analyzer. The received signals are passed to the developed image reconstruction method, which is designed to image backscattered signal energy as a function of location to get a clear image of the tumors. Due to the stark discrepancy in dielectric characteristics between normal and malignant tissue, the tumor location and its dimensions are effectively extracted from the scanned data. The proposed method is described completely with proper qualitative and quantitative analysis. The effectiveness of the image reconstruction method with the novel preprocessing stage is demonstrated by carefully imaging the developed phantoms. Multiple tumors implanted within the fat layer of the homogeneous breast phantom and multiple tumors embedded within the gland layer of the heterogeneous breast phantom are clearly identified. The proposed approach is shown to offer a significant improvement in performance over the conventional delay and sum (DAS) technique as explained based on the signal-to-mean ratio (SMR) metric.

关键词： Antipodal Vivaldi antenna (AVA) breast phantom heterogeneous homogeneous image reconstruction algorithm imaging setup malignant qualitative quantitative ultrawideband Antipodal Vivaldi antenna (AVA) breast phantom heterogeneous homogeneous image reconstruction algorithm imaging setup malignant qualitative quantitative ultrawideband

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Comparison of Different image reconstruction algorithms for Synthetic Transmit Aperture Imaging using Sparse Receiving Array

Comparison of Different Image Reconstruction Algorithms for ...

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IEEE International Ultrasonics Symposium (IUS)

作者： Gong, Ping Kolios, Michael C. Xu, Yuan Ryerson Univ Dept Phys Toronto ON Canada

ISBN: (纸本)9781479970490

Hadamard encoded Synthetic transmit aperture (H-STA) ultrasound imaging was proposed to provide RF signals with high signal-to-noise ratio (SNR). In this paper, the Hadamard encoded transmission was applied to designing a lowcost ultrasound imaging system by reducing the number of receiving channels and eliminating the delay circuit for transmission. However, reducing the receiving channels compromised the image qualities. To improve the image qualities, we proposed a reconstruction method: synthetic aperture subarray compounding (SASC). We compared the performance of three image reconstruction methods: regular synthetic aperture (SA) reconstruction, synthetic aperture compounding (SAC) and SASC. SASC presents a good balance between SA and SAC in terms of contrast-noise-ratio and contrast ratio of the hypoechoic inclusion.

关键词： Sparse Receiving Array Low-cost image reconstruction algorithm Synthetic Transmit Aperture Imaging Sub-array Compounding

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Effective Analysis of image reconstruction algorithms in Nuclear Medicine Using Fuzzy PROMETHEE

Effective Analysis of Image Reconstruction Algorithms in Nuc...

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Advances in Science and Engineering Technology International Conferences

作者： Dilber Uzun Ozsahin Nuhu Abdulhaqq Isa Berna Uzun Ilker Ozsahin Department of Biomedical Engineering Near East University Nicosia North-Cyprus Department of Mathematics Near East University Nicosia North-Cyprus

ISBN: (纸本)9781538624005

In medical imaging, the sets of projections obtained from either gamma radiation or X-radiation are converted into either a 2 dimensional (2D) or three dimensional (3D) images via a technique called image reconstruction. Nuclear medicine in particular employs this reconstruction technique to display the the image or radioisotope distribution within the patient's body. These techniques are integral part of the imaging modalities;they are complex computer algorithms which uses analytical or iterative methods to transform the generated projections into images. They come in various types and are characterized with certain features leading to the creation of image of diagnostic quality. Among these quality features are spatial resolution, variance, bias, contrast, noise etc. Availability of several reconstruction techniques makes it a huge task during the selection process of the best method for a particular modality. This study examines and compared the most commonly employed techniques using a Fuzzy-based Multi-criteria decision making method. This Fuzzy PROMETHEE method was employed in order to solve the decision making problems in nuclear imaging. Evaluation result showed that FBP is the alternative among the evaluated reconstruction techniques, due to its numerous distinct quality features. Furthermore, LM-OSEM was found to have the highest positive outranking flow.

关键词： Nuclear Medicine image reconstruction Fuzzy PROMETHEE image reconstruction algorithm image quality characteristics

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Overview on image reconstruction algorithms for Electrical Capacitance Tomography

Overview on Image Reconstruction Algorithms for Electrical C...

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第37届中国控制会议

作者： Gao Yanli Xu Qing Luo Kunming Guan Junjie East China Jiaotong University

Electrical Capacitance Tomography is an imaging technology for visualizing industrial process based on the mechanism of capacitance sensitive process. After decades of development, the research results of ECT technology are also constantly improved and further. However the soft-field effect and under-determined problem limited the ECT imaging technology applied in related field. There has been extensive effort to study the image reconstruction theory and algorithms, in order to significantly improve the image resolution and speed to extend the application of ECT technique. This paper mainly gives an overview for the current research status of image reconstruction algorithm and compares the shortcoming and advantages of the iterative reconstruction algorithms, the non-iterative reconstruction algorithms and intelligent algorithms. In the end, Several 3 D image reconstruction algorithms are introduced and the future research direction of image reconstruction algorithm are discussed.

关键词： Electrical capacitance tomography image reconstruction algorithm 3D image reconstruction

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A Novel image reconstruction Strategy for ECT: Combining Two algorithms With a Graph Cut Method

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2020年第3期69卷 804-814页

作者： Guo, Qiang Li, Xue Hou, Baolin Mariethoz, Gregoire Ye, Mao Yang, Wuqiang Liu, Zhongmin Chinese Acad Sci Dalian Inst Chem Phys Dalian Natl Lab Clean Energy Dalian 116023 Peoples R China Chinese Acad Sci Dalian Inst Chem Phys Natl Engn Lab MTO Dalian 116023 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Chinese Acad Sci Dalian Inst Chem Phys State Key Lab Catalysis Dalian 116023 Peoples R China Univ Lausanne Inst Earth Surface Dynam CH-1015 Lausanne Switzerland Chinese Acad Sci Dalian Inst Chem Phys Dalian Natl Lab Clean Energy Dalian 116023 Peoples R China Chinese Acad Sci Dalian Inst Chem Phys Natl Engn Lab MTO Dalian 116023 Peoples R China Univ Manchester Sch Elect & Elect Engn Manchester M13 9PL Lancs England

image reconstruction plays a key role in the application of electrical capacitance tomography (ECT). Although many different algorithms have been developed in the past, it is often difficult to obtain satisfactory images in all imaging regions by the use of a single algorithm due to the soft-field nature of ECT. This motivated us to develop a novel ECT image reconstruction strategy, in which a high-quality image can be obtained by combining the images reconstructed by two different algorithms via a graph cut method. By doing so, it is possible to retain the advantage of each algorithm for specified imaging regions and improve the quality of the whole image. This strategy was verified both numerically and experimentally for two widely used ECT reconstruction algorithms, i.e., linear backprojection and Tikhonov regularization. The results for stationary objects as well as gas-solid fluidized beds demonstrated that this graph-cut-based combination strategy presents a promising approach for ECT image reconstruction.

关键词： Electrical capacitance tomography (ECT) graph cut image reconstruction algorithm linear backprojection (LBP) Tikhonov regularization (TR)

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Comparison of different image reconstruction algorithms for synthetic transmit aperture imaging using sparse receiving array

Comparison of different image reconstruction algorithms for ...

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IEEE International Ultrasonics Symposium

作者： Ping Gong Michael C. Kolios Yuan Xu Physics Department Ryerson University Toronto Canada

ISBN: (纸本)9781479970506

Hadamard encoded Synthetic transmit aperture (H-STA) ultrasound imaging was proposed to provide RF signals with high signal-to-noise ratio (SNR). In this paper, the Hadamard encoded transmission was applied to designing a low-cost ultrasound imaging system by reducing the number of receiving channels and eliminating the delay circuit for transmission. However, reducing the receiving channels compromised the image qualities. To improve the image qualities, we proposed a reconstruction method: synthetic aperture sub-array compounding (SASC). We compared the performance of three image reconstruction methods: regular synthetic aperture (SA) reconstruction, synthetic aperture compounding (SAC) and SASC. SASC presents a good balance between SA and SAC in terms of contrast-noise-ratio and contrast ratio of the hypo-echoic inclusion.

关键词： Sparse Receiving Array Low-cost image reconstruction algorithm Synthetic Transmit Aperture Imaging Sub-array Compounding

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Deep Learning image reconstruction Simulation for Electromagnetic Tomography

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IEEE SENSORS JOURNAL 2018年第8期18卷 3290-3298页

作者： Xiao, Jun Liu, Ze Zhao, Pengfei Li, Yong Huo, Jiwei Beijing Jiaotong Univ Coll Elect & Informat Engn Beijing 100044 Peoples R China

In the inverse problem of tomography field, the solution of image reconstruction is often ill-posed and the prior information about imaging features is limited. We expect to learn imaging autonomously by learning algorithms and representative samples. So in this paper, two deep learning image reconstruction algorithms SSAE+RBF and optimized fully connected (FC) are proposed to learn imaging in electromagnetic tomography (EMT). It is a preliminary attempt of sample training algorithm in EMT. Furthermore, a loss function is proposed and 30 000 image samples for training, verification, and test are designed. Simulation experiments show the following. First, for the 26 000 training samples, both of two algorithms have the ability to basically reproduce the actual distribution of object field. Second, for the random 2000 test samples, which has similar type with training sample but doesn't learned, both of the two algorithms are superior to the traditional algorithms in image reconstruction. In addition, the mean value of image correlation coefficient (ICC) and relative image error are 0.817 and 0.530 for optimized FC network without noise. Third, when 0%-7% noise levels are added to the test set, the standard deviation of ICC in two algorithms are 0.007 and 0.040. To a certain extent, it proves the robustness of these networks. Fourth, in addition, our deep learning algorithm has an advantage in computing speed with graphic processing unit.

关键词： Electromagnetic tomography inverse problem image reconstruction algorithm deep learning neural network

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A New image reconstruction Method for Electrical Charge Tomography System

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2012年第6期37卷 1625-1643页

作者： Rahmat, Mohd Fua'ad Isa, Mohd Daud Hussin, Tengku Ahmad B. S. Raja Univ Teknologi Malaysia Control & Instrumentat Engn Dept Fac Elect Engn Johor Baharu 81310 Johor Malaysia Politeknik Kota Bharu Dept Elect Engn Kota Baharu 16450 Kelantan Malaysia Politeknik Kota Bharu Gen Studies Dept Kota Baharu 16400 Kelantan Malaysia

image reconstruction is vital for process tomography system. Due to industrial demand for process monitoring and control of solid transport in pneumatic conveyor, electrical charge tomography system using electrostatic charge carried by particles has become vital and attract the attention of many researchers. Three image reconstruction algorithm methods known as linear back projection, filtered back projection and least square methods are actively discussed by researchers. In this paper, a new image reconstruction algorithm called least square with regularization (LSR) method will be introduced to improve the previously mentioned method applied in electrical charge tomography. Simulation and experimental data had been used to reconstruct the image. The results were compared and it indicated that LSR method showed better improvement in terms of stability and accuracy of the image.

关键词： Electrical charge tomography image reconstruction algorithm Linear back projection Filtered back projection Least square Regularization

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image reconstruction for Electrical Impedance Tomography: Experimental Comparison of Radial Basis Neural Network and Gauss – Newton Method

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IFAC-PapersOnLine 2018年第6期51卷 438-443页

作者： Hrabuska, Radek Prauzek, Michal Venclikova, Marketa Konecny, Jaromir Department of Cybernetics and Biomedical Engineering VSB-Technical University of Ostrava Ostrava-Poruba70833 Czech Republic

Electrical impedance tomography (EIT) is an intensively researched noninvasive diagnostic method for medical use, that can help to improve the lung diagnostics, artificial lung ventilation and prevent lung injuries. Further improvements of reconstruction algorithms and measurement devices are essential to widen the use of EIT as a lung diagnostic method. To test potential of Radial Basis Neural Networks (RBNN) and Hopfield Neural Networks (HNN) for image reconstruction experiment is carried. Said neural networks are compared with Gauss – Newton (GN) algorithm. Results of the experiment show higher reconstruction accuracy with RBNN and HNN over GN algorithm. © 2018

关键词： image reconstruction Artificial organs Biological organs Chemical sensors Diagnosis Electric impedance Electric impedance measurement Electric impedance tomography Hopfield neural networks Neural networks Newton Raphson method Noninvasive medical procedures Radial basis function networks Artificial lung ventilation Electrical impe dance tomography (EIT) Electrical impedance tomography Hopfield neural networks (HNN) image reconstruction algorithm Non invasive diagnostics Radial basis neural networks reconstruction algorithms

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New image reconstruction method in dynamic electrical impedance tomography 3

New image reconstruction method in dynamic electrical impeda...

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Conference on Electronic Imaging and Multimedia Technology III

作者： Hou, WD Mo, WL Shanghai Univ Dept Commun Engn Shanghai 200072 Peoples R China

ISBN: (纸本)0819447145

image reconstruction in electrical impedance tomography (EIT) is a non-linear inverse problem. The linear model is always used in most of the reconstruction algorithm in dynamic EIT, which causes large errors of image reconstruction. In this paper, we proposed a new image reconstruction method in dynamic Ell In the method the artificial neural network based on the error back propagation algorithm (BP ANN) is used to express the non-linear relation between the impedance change position inside the measured object and the voltage change value measured on the surface of the object. Thus, the location of the impedance change can be decided by the measured voltage change on the surface, and then the impedance change image will be reconstructed with linear approximated method. The reconstructed error will be decreased largely, because the impedance change position can be detected precisely by our proposed method. The experimental results indicate that the precision of the reconstructed image with our method is greatly higher than that with the back projection method.

关键词： image reconstruction algorithm neural network electrical impedance tomography biomedical imaging

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