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8th Conference on Biomedical Thermoacoustics, Optoacoustics and Acousto-optics

作者： Jiang, Huabei Yuan, Zhen Yin, Lu Wang, Qiang Zhang, Qizhi Univ Florida J Crayton Pruitt Family Dept Biomed Engn Gainesville FL 32611 USA

ISBN: (纸本)9780819465504

We present experimental evidence that the optical absorption coefficient images of heterogeneous media can be obtained with quantitative photoacoustic tomography (PAT). Photoacoustic images are obtained from a series of tissue-like phantom experiments using a finite element-based reconstruction algorithm coupled with a scanning photoacoustic imaging system. The experimental results show that optical absorption images can be quantitatively reconstructed when the photon diffusion model is coupled with the Helmholtz photoacoustic wave equation.

关键词： photoacoustic tomography imaging reconstruction algorithm

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Object Detection Based on Electrical Capacitance Tomography 10

Object Detection Based on Electrical Capacitance Tomography

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IEEE Sensors Applications Symposium (SAS)

作者： Muehlbacher-Karrer, Stephan Zangl, Hubert Alpen Adria Univ Inst Smart Syst Technol Sensors & Actuators A-9020 Klagenfurt Austria

ISBN: (纸本)9781479961177

Robust object detection and low computational effort are two key issues, which have to be addressed when Electrical Capacitance Tomography (ECT) is applied in the field of mobile applications. In this paper we present an object detection technique in combination with an artefact reduced fast reconstruction algorithm. The approach achieves a high object detection rate in the vicinity and center of the sensor front end. The proposed light-weight signal processing chain is the key to integrate this sensing technology on a platform limited in terms of space, energy and computational resources.

关键词： Object detection Electrical capacitance tomography inspection technique Sensing Techniques Mobile Applications reconstruction algorithm handicrafts

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Application of Compressed Sensing to Radar Signals 33

Application of Compressed Sensing to Radar Signals

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33rd International Conference on Radioelektronika (RADIOELEKTRONIKA)

作者： Perd'och, Jozef Pacek, Miroslav Matousek, Zdenek Gazovova, Stanislava Armed Forces Acad Gen MR Stefanik Dept Elect Liptovsky Mikulas Slovakia

ISBN: (纸本)9798350398342

This paper presents the application of compressed sensing techniques on radar echo signals. reconstruction algorithms, specifically Orthogonal Matching Pursuit (OMP), Compressive Sampling Matching Pursuit (CoSAMP), and Fast Iterative Shrinkage-Thresholding algorithm (FISTA) are used without dictionary learning in this paper. The abovementioned reconstruction algorithms were tested for two Compression Ratio values. To verify the results of all the reconstruction algorithms, the modified Cell-Averaging Constant False Alarm Rate (CA-CFAR) was applied to both, the original radar data, and the reconstructed radar data. For the simulation purpose, synthetic radar signals with different Signal-to-Noise Ratio (SNR) values were used. The best results were achieved using the FISTA algorithm.

关键词： compressed sensing sparse sensing radar signal processing reconstruction algorithm

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Power-Efficient RMA SAR Imaging Using Pipelined Non-Uniform Fast Fourier Transform

Power-Efficient RMA SAR Imaging Using Pipelined Non-Uniform ...

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IEEE International Radar Conference (RadarCon)

作者： Nash, Gregory T. Cheema, Umer I. Ansari, Rashid Khokhar, Ashfaq A. Univ Illinois Dept Elect & Comp Engn Chicago IL USA IIT Dept Elect & Comp Engn Chicago IL 60616 USA

ISBN: (纸本)9781479982325

Range Migration algorithm (RMA) is one of the most practiced frequency domain based algorithms for Synthetic Aperture Radar (SAR) image reconstruction. While computationally more intensive than Polar Format algorithm (PFA), it has superior image reconstruction for large squint angles. Due to the real-time nature of SAR imaging-related tasks, it is desired to have faster hardware implementations of reconstruction algorithms. In this paper we study FPGA-based implementation of the RMA algorithm using a novel pipelined Non-uniform FFT (NuFFT) module that optimizes its operation by exploiting the order in which samples are presented. We demonstrate that we can achieve processing speed of over 600 Msps (Mega Samples per Second) for the implemented RMA algorithm using the FPGA.

关键词： Jabiluka Uranium Mine Ranger Uranium Mine Regional Monitoring Agency image reconstruction Fourier Transform reconstruction algorithm Fast Fourier transform Radar polarimetry Synthetic aperture radar Field programmable gate arrays Frequency-domain analysis

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Optimization of shutter scan parameters in digital tomosynthesis system

Optimization of shutter scan parameters in digital tomosynth...

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Conference on Medical Imaging - Physics of Medical Imaging

作者： Kim, Dohyeon Lee, Donghoon Lee, Haenghwa Choi, Sunghoon Choi, Seungyeon Chao, Zhen Kim, Hee-joung Yonsei Univ Dept Radiat Convergence Engn Coll Hlth Sci Wonju South Korea Yonsei Univ Dept Radiol Sci Wonju South Korea Yonsei Univ Res Inst Hlth Sci Wonju South Korea

ISBN: (数字)9781510616363

ISBN: (纸本)9781510616363

In medical imaging field, various dose reduction techniques have been studied. We proposed shutter scan acquisition for region of interest (ROI) imaging to reduce the patient exposure dose in digital tomosynthesis system. Projections obtained by shutter scan acquisition is a combination of truncated projections and non-truncated projections. In this study, we call the number of truncated projections divided by the number of non-truncated projections as shutter weighting factor. The shutter scan acquisition parameters were optimized using 5 different acquisition sets with the shutter weighting factor (0.16, 0.35, 1.03, 3.05 and 7.1). A prototype CDT system (LISTEM, Korea) and the LUNGMAN phantom (Kyoto Kagaku, Japan) with an 8 mm lung nodule were used. A total of 81 projections with shutter scan acquisition were obtained in 5 sets according to shutter weighting factor. The image quality was investigated using the contrast noise ratio (CNR). We also calculated figure of merit (FOM) to determine optimal acquisition parameters for the shutter scan acquisition. The ROI of the reconstructed image with shutter scan acquisition showed enhanced contrast. The highest CNR and FOM value, shutter weighting factor 7.1, is the acquisition set consisting of 71 truncated projections and 10 non-truncated projections. In this study, we investigated the effects of composition ratio of the truncated and non-truncated projections on reconstructed images through the shutter scan acquisition. In addition, the optimal acquisition conditions for the shutter scan acquisition were determined by deriving the FOM values. In conclusion, we can suggest optimal shutter scan acquisition parameters on the lesion within the ROI to be diagnosed.

关键词： ROI imaging dose reduction digital tomosynthesis system optimization reconstruction algorithm acquisition method

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Signal sampling and recovery under long-memory errors

Signal sampling and recovery under long-memory errors

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IEEE International Symposium on Information Theory

作者： Pawlak, M Stadtmüller, U Univ Manitoba Dept Elect & Comp Engn Winnipeg MB R3T 5V6 Canada

The post-filtering modification of the Whittaker-Shannon interpolation series in the presence of long-memory errors is examined. The pointwise and global rates of convergence of the reconstruction algorithm are evalua... 详细信息

ISBN: (纸本)0780382803

关键词： filtering theory convergence of numerical methods signal sampling signal reconstruction mean square error methods post-filtering modification Whittaker-Shannon interpolation series pointwise-global rate convergence reconstruction algorithm

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Generalized k-t BLAST and k-t SENSE using focuss

Generalized k-t BLAST and k-t SENSE using focuss

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4th IEEE International Symposium on Biomedical Imaging

作者： Jung, Hong Yoo, Jaeheung Ye, Jong Chul Korea Adv Inst Sci & Technol Taejon 305701 South Korea

ISBN: (纸本)9781424406715

According to the recent theory of compressed sensing, accurate reconstruction is possible even from data samples dramatically smaller than Nyquist sampling limit as long as the unknown image is sparse. In MRI, dynamic imaging such as cardiac cine may be a nice application of the compressed sensing theory since it requires significant reduction of data acquisition time whereas the periodic motions are usually sparse in spectral domain. The main contribution of this paper is to show that a sparse reconstruction method called the FOCal Underdetermined System Solver (FOCUSS) is a very effective compressed sensing reconstruction algorithm by exploiting the sparsity in spectral domain. Furthermore, our analysis reveals that celebrated k-t BLAST and k-t SENSE are special cases of our algorithm;hence our algorithm outperforms them in general situations.

关键词： Compressed sensing blasts blight reconstruction algorithm Spectral domain Data sampling

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Noise2Filter: fast, self-supervised learning and real-time reconstruction for 3D computed tomography

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MACHINE LEARNING-SCIENCE AND TECHNOLOGY 2021年第1期2卷

作者： Lagerwerf, Marinus J. Hendriksen, Allard A. Buurlage, Jan-Willem Batenburg, K. Joost Ctr Wiskunde & Informat Computat Imaging Grp NL-1098 XG Amsterdam Netherlands Leiden Univ Leiden Inst Adv Comp Sci NL-2333 CA Leiden Netherlands

At x-ray beamlines of synchrotron light sources, the achievable time-resolution for 3D tomographic imaging of the interior of an object has been reduced to a fraction of a second, enabling rapidly changing structures to be examined. The associated data acquisition rates require sizable computational resources for reconstruction. Therefore, full 3D reconstruction of the object is usually performed after the scan has completed. Quasi-3D reconstruction-where several interactive 2D slices are computed instead of a 3D volume-has been shown to be significantly more efficient, and can enable the real-time reconstruction and visualization of the interior. However, quasi-3D reconstruction relies on filtered backprojection type algorithms, which are typically sensitive to measurement noise. To overcome this issue, we propose Noise2Filter, a learned filter method that can be trained using only the measured data, and does not require any additional training data. This method combines quasi-3D reconstruction, learned filters, and self-supervised learning to derive a tomographic reconstruction method that can be trained in under a minute and evaluated in real-time. We show limited loss of accuracy compared to training with additional training data, and improved accuracy compared to standard filter-based methods.

关键词： computed tomography reconstruction algorithm real-time machine learning self-supervised learning filtered backprojection denoising

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How reliable are texture measurements?

How reliable are texture measurements?

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Conference on Medical Imaging - Physics of Medical Imaging

作者： Robins, Marthony Solomon, Justin Hoye, Jocelyn Abadi, Ehsan Marin, Daniele Samei, Ehsan Carl E Ravin Adv Imaging Labs Durham NC 27705 USA Med Phys Grad Program Durham NC 27705 USA Dept Radiol Durham NC 27705 USA Duke Univ Med Ctr Durham NC 27705 USA

ISBN: (数字)9781510616363

ISBN: (纸本)9781510616363

The purpose of this study was to assess the bias (objectivity) and variability (robustness) of computed tomography (CT) texture features (internal heterogeneities) across a series of image acquisition settings and reconstruction algorithms. We simulated a series of CT images using a computational phantom with anatomically-informed texture. 288 clinically-relevant simulation conditions were generated representing three slice thicknesses (0.625, 1.25, 2.5 mm), four in-plane pixel sizes (0.4, 0.5, 0.7, 0.9 mm), three dose levels (CTDIvol = 1.90, 3.75, 7.50 mGy), and 8 reconstruction kernels. Each texture feature was sampled with 4 unique volumes of interest (VOIs) (244, 1953, 15625, 125000 mm(3)). Twenty-one statistical texture features were calculated and compared between the ground truth phantom (i.e., pre-imaging) and its corresponding post-imaging simulations. Metrics of comparison included (1) the percent relative difference (PRD) between the post-imaging simulation and the ground truth, and (2) the coefficient of variation (%COV) across simulated instances of texture features. The PRD and %COV ranged from -100% to 4500%, and 0.8% to 49%, respectively. PRD decreased with increased slice thickness, in-plane pixel size, and dose. The dynamic range of results indicate that image acquisition and reconstruction conditions (i.e., slice thicknesses, in-plane pixel sizes, dose levels, and reconstruction kernels) can lead to significant bias and variability in texture feature measurements.

关键词： CT simulation texture features radiomics voxel size slice thickness reconstruction algorithm

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ANALYSIS IN THEORY AND TECHNOLOGY APPLICATION OF COMPRESSIVE SENSING 6

ANALYSIS IN THEORY AND TECHNOLOGY APPLICATION OF COMPRESSIVE...

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6th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)

作者： Jiang, Jin Chen, Changxing Air Force Engn Univ Sch Sci Xian Peoples R China

ISBN: (纸本)9781479949557

With the information demand increasing, the method which based on Nyquist sampling is expensive and low efficiency in ultra wideband signal processing. To extract before transmission data storage can cause a lot of waste resources. Compressive Sensing can make sampling and compression at the same time. The sampling frequency is far less than the Nyquist sampling frequency as long as the signal is sparse in a domain. It can deal with discrete signal directly and take a few values for processing from n dimension discrete signal. Some algorithm is used to recover on the receiving-end. A compressive Sensing method is proposed in this paper to reduce the requirement of the system in sampling rate. Firstly, the CS basic theory is introduced and three key technologies are summarized: sparse representation of signals;the design of the measurement matrix;compressive sensing reconstruction algorithm. Then the application of compressive sensing technology in specific areas is introduced.

关键词： Nyquist Sampling Compressive Sensing (CS) Restricted Isometry Property (RIP) Sparse Representation reconstruction algorithm

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