Universal plane wave compounding for high quality us imaging using deep learning
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Plane-wave compounding is to sum up several successive plane waves incident at different angles to form an image. By applying time-reversal of the received signals, transmit focusing can be synthesized. Unfortunately, to improve the temporal resolution, the number of plane waves should be reduced, which often degrades the image quality. To address this problem, an image domain learning method using neural networks has been proposed, but the network needs to be retrained when the number of plane waves changes. Herein, we propose, for the first time, a universal plane-wave compounding scheme using deep learning to directly process plane waves and RF data acquired at different view angles and sub-sampling rate to generate high quality US images.
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This document presents an image compression technique using Haar wavelet transforms. It begins with background on the need for image compression due to increasing image sizes. It then outlines the encoder and decoder block diagrams and classifications of compression techniques. The key aspects of the proposed technique are presented: using wavelet transforms to exploit spatial and frequency correlations, applying averaging and differencing operations on rows and columns, thresholding the transformed matrix, and reconstructing the original image. Advantages include conceptual simplicity, speed, memory efficiency and reversibility. Results and future work are discussed before concluding on the benefits of wavelet-based compression.
Depth estimation do we need to throw old things away
발표의 개요 : Human visual system 기반의 CNN for depth estimation과 CNN inspired by conventional methods
Case1: Cross-channel stereo matching
Case2: Depth from light field
Case3: Multiview stereo
Conclusion
Ip unit 3 modified of 26.06.2021
This document discusses image restoration and contains summaries of several lecture slides on image degradation and restoration models, noise models, and frequency domain filtering techniques for periodic noise reduction. It was compiled by Dr. Radhey Shyam with contributions from Dr. Philippe Cattin, and is intended for academic use by students to help explain basic concepts of image restoration.
DETECTION OF POWER-LINES IN COMPLEX NATURAL SURROUNDINGS
Power transmission line inspection using Unmanned Aerial Vehicles (UAV) is taking off as an exciting solution due to advances in sensors and flight technology. Extracting power-lines from aerial images, taken from the UAV, having complex natural surroundings is a critical task in the above problem. In this paper we propose an approach for suppressing natural surrounding that
leads to power line detection. The results of applying our method on real-life video frames taken from a UAV demonstrate that our approach is very effective. We believe that our approach can
be easily used for line detection in any other real outdoor video as well.
Optical CT scan
This document discusses an optical computed tomography (CT) scan project. It begins with an abstract that outlines how CT is used in medical and industrial applications. It then describes how the project aimed to reconstruct a previous student's CT device using a laser light source and photodiode detector. Iterative reconstruction methods combined with the Radon and inverse Radon transforms were used to obtain 2D slice images from multiple projections of a sample.
Massive MIMO Measurements - 128x12 at 3.5GHz
This document summarizes an experiment conducted using a 128-antenna massive MIMO testbed operating at 3.51GHz. Initial measurements were taken in an indoor atrium using 12 user equipment placed at varying distances from the base station antenna array. The results showed excellent spatial orthogonality between users even under line-of-sight conditions, achieving a sum-rate of 1.59Gbps across 20MHz of bandwidth. Ongoing work includes real-time downlink evaluation, power control optimization, and deployment of the system across a citywide fiber network.
A Novel Blind SR Method to Improve the Spatial Resolution of Real Life Video ...
This document proposes a novel blind super resolution method to improve the spatial resolution of real-life video sequences. The key aspects of the proposed method are:
1) It estimates blur without knowing the point spread function or noise statistics using a non-uniform interpolation super resolution method and multi-scale processing.
2) It uses a cost function with fidelity and regularization terms of a Huber-Markov random field to preserve edges and fine details in the reconstructed high resolution frames.
3) It performs masking to suppress artifacts from inaccurate motions, adaptively weighting the fidelity term at each iteration for faster convergence.
The method is tested on real-life videos with complex motions, objects, and brightness changes, showing
A Study of Total-Variation Based Noise-Reduction Algorithms For Low-Dose Cone...
In low-dose cone-beam computed tomography, the reconstructed image is contaminated with
excessive quantum noise. In this work, we examined the performance of two popular noisereduction
algorithms—total-variation based on the split Bregman (TVSB) and total-variation based
on Nesterov’s method (TVN)—on noisy imaging data from a computer-simulated Shepp–Logan
phantom, a physical CATPHAN phantom and head-and-neck patient. Up to 15% Gaussian noise
was added to the Shepp–Logan phantom. The CATPHAN phantom was scanned by a Varian OBI
system with scanning parameters 100 kVp, 4 ms, and 20 mA. Images from the head-and-neck
patient were generated by the same scanner, but with a 20-ms pulse time. The 4-ms low-dose
image of the head-and-neck patient was simulated by adding Poisson noise to the 20-ms image.
The performance of these two algorithms was quantitatively compared by computing the peak
signal-to-noise ratio (PSNR), contrast-to-noise ratio (CNR) and the total computational time. For
CATPHAN, PSNR improved by 2.3 dB and 3.1 dB with respect to the low-dose noisy image for the
TVSB and TVN based methods, respectively. The maximum enhancement ratio of CNR for
CATPHAN was 4.6 and 4.8 for TVSB and TVN respectively. For data for head-and-neck patient,
the PSNR improvement was 2.7 dB and 3.4 dB for TVSB and TVN respectively. Convergence
speed for the TVSB-based method was comparatively slower than TVN method. We conclude that
TVN algorithm has more desirable properties than TVSB for image denoising.
Wavelet based image compression technique
This document summarizes a presentation on wavelet based image compression. It begins with an introduction to image compression, describing why it is needed and common techniques like lossy and lossless compression. It then discusses wavelet transforms and how they are applied to image compression. Several research papers on wavelet compression techniques are reviewed and key advantages like higher compression ratios while maintaining image quality are highlighted. Applications of wavelet compression in areas like biomedicine and multimedia are presented before concluding with references.
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Image Denoising Based On Wavelet for Satellite Imagery: A Review
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NIR Three dimensional imaging of breast model using f-DOT
NIR Three dimensional imaging of breast model using f-DOT
M.Tech project on Haar wavelet based approach for image compression
M.Tech project on Haar wavelet based approach for image compression
Depth estimation do we need to throw old things away
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DETECTION OF POWER-LINES IN COMPLEX NATURAL SURROUNDINGS
DETECTION OF POWER-LINES IN COMPLEX NATURAL SURROUNDINGS
A Novel Blind SR Method to Improve the Spatial Resolution of Real Life Video ...
A Novel Blind SR Method to Improve the Spatial Resolution of Real Life Video ...
A Study of Total-Variation Based Noise-Reduction Algorithms For Low-Dose Cone...
A Study of Total-Variation Based Noise-Reduction Algorithms For Low-Dose Cone...
Similar to Universal plane wave compounding for high quality us imaging using deep learning
Beamforming antennas (1)
The document discusses beamforming antennas and their applications. It begins by outlining beamforming concepts and configurations like phased arrays and adaptive arrays. It then discusses applications of beamforming antennas in areas like radar, sonar, communications and imaging. Specific examples covered include phased array radar, neuronal spike sorting, and smart antenna systems for wireless networks. Vector antennas and their advantages over phased arrays are also summarized. Finally, the document discusses potential uses and challenges of beamforming antennas for wireless ad hoc networks.
KinPhy
KinPhy is a kinetic in-band channel for millimeter-wave networks that uses physically oscillating metasurfaces to backscatter information to an mm-wave router (1). It consists of a metasurface and radar reader (2). The metasurface precisely modulates the phase of reflected mm-wave signals using piezo actuators, while the reader shines a mm-wave signal onto the surface and decodes the backscattered signal (3). Evaluation shows the system can accurately detect metasurfaces at distances up to 5m indoors, even when non-line-of-sight or facing away, demonstrating potential for applications like spontaneous authentication and security.
"An adaptive modular approach to the mining of sensor network ...
This document summarizes an adaptive modular approach for mining sensor network data using machine learning techniques. It presents a two-layer architecture that uses an online compression algorithm (PCA) in the first layer to reduce data dimensionality and an adaptive lazy learning algorithm (KNN) in the second layer for prediction and regression tasks. Simulation results on a wave propagation dataset show the approach can handle non-stationarities like concept drift, sensor failures and network changes in an efficient and adaptive manner.
Three dimensional particle image velocimetry
Three-dimensional particle image velocimetry for the flows near the wall. A brief introduction to measurement methods in fluid fields in general and imaging methods in particular. A general overview of famous three-dimensional particle imaging methods and detailed description of image velocimetry for the near wall flows
beamformingantennas1-150723193911-lva1-app6892.pdf
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MULTI-DOMAIN UNPAIRED ULTRASOUND IMAGE ARTIFACT REMOVAL USING A SINGLE CONVOL...
MULTI-DOMAIN UNPAIRED ULTRASOUND IMAGE ARTIFACT REMOVAL USING A SINGLE CONVOLUTIONAL NEURAL NETWORK
CSI Acquisition for FDD-based Massive MIMO Systems
II International Workshop on Challenges and Trends on Broadband Wireless Mobile Access Networks – Beyond LTE-A
Channel Models for Massive MIMO
II International Workshop on Challenges and Trends on Broadband Wireless Mobile Access Networks – Beyond LTE-A
ieee nss mic 2016 poster N30-21
ieee nss mic 2016 poster N30-21
Pixel Discrimination using Artificial Neural Network for Gamma Camera Module
MTECH 3RD SEM PPT-1.pptx
This document presents a master's thesis on the design and implementation of a multilayer microstrip log periodic dipole antenna. It includes sections on introduction, literature review, problem identification, performance evaluation, proposed methodology, results and discussion, and conclusions. The literature review analyzes several previous research papers on log periodic dipole antennas. The proposed methodology section outlines the design process, including mathematical modeling, simulation software, and fabrication. The results section presents the antenna geometry and performance metrics for two proposed multilayer designs using different materials. Both designs achieved improved bandwidth and return loss compared to previous designs. The conclusion discusses achieving further enhancement of antenna parameters through new multilayer configurations and materials.
Mimo radar detection in compound gaussian clutter using orthogonal discrete f...
This paper proposes orthogonal Discrete Frequency Coding Space Time Waveforms (DFCSTW) for
Multiple Input and Multiple Output (MIMO) radar detection in compound Gaussian clutter. The proposed
orthogonal waveforms are designed considering the position and angle of the transmitting antenna when
viewed from origin. These orthogonally optimized show good resolution in spikier clutter with Generalized
Likelihood Ratio Test (GLRT) detector. The simulation results show that this waveform provides better
detection performance in spikier Clutter.
SMART TRANSMITTER AND RECEIVER FOR UNDERWATER
College seminar presentation made by RITU BHARTI in 2016 ,college PADMANAVA COLLEGE OF ENGINEERING,ROURKELA,ODISHA
Coastal erosion management using image processing and Node Oriented Programming
Presentation of my Thesis with the title "Coastal erosion management using image processing and Node Oriented Programming" for achieving my Masters Degree in Computer and Automation Engineering from Siena University, Italy.
Bandwidth Enhancement in Multimode Polymer Waveguides Using Waveguide Layout ...
Dispersion studies demonstrate that waveguide layout can be used to enhance the bandwidth performance of multimode polymer waveguides for use in board-level optical interconnects, providing >40 GHz.m without the need for any launch conditioning.
Deep Learning Tomography
This document discusses using deep learning for seismic tomography. It begins with an overview of seismic tomography and the forward and inverse problems. It then discusses using deep learning approaches like empirical risk minimization with neural networks to solve the inverse problem. Several deep learning architectures are evaluated including those using semblance cubes, spectrograms of raw seismic data, and raw seismic data directly as input. Recurrent neural networks with LSTM and GRU cells are also explored for image reconstruction. The document concludes that while performance is good on simple models, more data and increased network capacity is needed for complex geology. It also lists several related publications.
DCS-IGARSS11_v2-aguilera.ppt
Compressed sensing techniques can be used to reconstruct 3D tomographic images from polarimetric synthetic aperture radar (SAR) data using fewer measurements than required by conventional beamforming. Single signal compressed sensing recovers complex reflectivities from a reduced number of tracks but has issues modeling polarimetry. Multiple signal compressed sensing exploits correlations between polarimetric channels and azimuth-range positions for improved reconstruction probability and robustness to noise. Compressed sensing combined with a wavelet-based sparse vegetation model shows potential for high-resolution volumetric imaging of forest canopies from fewer SAR acquisition tracks.
US_pres.pptx
This document provides an overview of synthetic aperture ultrasound imaging. It begins with a brief introduction of conventional ultrasound imaging and its limitations. It then describes the theory behind synthetic aperture imaging, which uses a single transducer element to transmit spherical waves across the entire region of interest and receives signals from all transducer elements to synthesize a larger aperture. The document discusses several key aspects of synthetic aperture imaging implementation including beamforming, resolution, apodization, and backpropagation techniques. It presents results from simulations demonstrating improved angular resolution compared to conventional imaging. Finally, it discusses challenges and potential solutions for real-time implementation including using FPGA and GPU architectures.
Xray interferometry
This document discusses the concept of an X-ray interferometer called MAXIM that could achieve micro-arcsecond resolution. It would consist of an optics spacecraft holding multiple flat mirrors in formation with a detector spacecraft to form interference patterns. The goal is to image phenomena like black hole accretion disks and supernovae with much higher resolution than current telescopes. A pathfinder mission is proposed with 100 microarcsecond resolution using two spacecraft separated by 1.4 meters as a technology demonstration.
SIXTEEN CHANNEL, NON-SCANNING AIRBORNE LIDAR SURFACE TOPOGRAPHY (LIST) SIMULATOR
This document describes the development of an airborne lidar instrument called A-LISTS to demonstrate technologies for a proposed spaceborne lidar mission called LIST. LIST aims to map global topography at 5m resolution to study Earth's surface and changes over time. A-LISTS will test a multi-beam laser transmitter, high sensitivity detectors, and data processing to achieve LIST measurement capabilities from an aircraft. Its first flight in September 2011 will collect lidar data over various terrain to evaluate performance. Key challenges for LIST that A-LISTS helps address include detecting ground returns through vegetation canopies and developing efficient, lightweight instruments.
Alternatives to Point-Scan Confocal Microscopy
There are three main types of confocal microscopic systems - point scanning confocal systems, area scanning confocal systems, and fluorescence grating imager systems. Area scanning systems use a multi-pinhole spinning disk to provide faster scan speeds compared to point scanning systems. Fluorescence grating imager systems use a movable grating and multiple exposures to optically section specimens in a conventionally illuminated microscope without physical sectioning.
Similar to Universal plane wave compounding for high quality us imaging using deep learning (20)
"An adaptive modular approach to the mining of sensor network ...
"An adaptive modular approach to the mining of sensor network ...
beamformingantennas1-150723193911-lva1-app6892.pdf
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Coastal erosion management using image processing and Node Oriented Programming
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Bandwidth Enhancement in Multimode Polymer Waveguides Using Waveguide Layout ...
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SIXTEEN CHANNEL, NON-SCANNING AIRBORNE LIDAR SURFACE TOPOGRAPHY (LIST) SIMULATOR
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Essentials of Automations: The Art of Triggers and Actions in FME
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
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TrustArc Webinar - 2024 Global Privacy Survey
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
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Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
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Climate Impact of Software Testing at Nordic Testing Days
My slides at Nordic Testing Days 6.6.2024
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Removing Uninteresting Bytes in Software Fuzzing
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
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Artificial Intelligence for XMLDevelopment
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HCL Notes and Domino License Cost Reduction in the World of DLAU
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Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
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Universal plane wave compounding for high quality us imaging using deep learning
- 1. Universal Plane-Wave Compounding for High Quality US Imaging Using Deep Learning Shujaat Khan, Jaeyoung Huh and Jong Chul Ye BISPL - BioImaging, Signal Processing, and Learning lab. KAIST, Korea Presented in: 2019 IEEE International Ultrasonics Symposium (IUS)
- 2. Motivation Application Needs Reduce the number of channel - Ultra-fast US - Portable US - 3 dimensional US
- 3. Acquisition Modes Focused Imaging Planewave Imaging
- 4. Conventional approach Conventional delay-and-sum (DAS) Beamforming Pipeline Rx probe Beam focusing Signal Adder Envelope detection Log compression B-mode image Hilbert Transform IQ data (signal before envelope detection)
- 5. Full-sampling pattern Our contribution Beam focusing Envelope detection Log compression B-mode image IQ data (signal before envelope detection) Convolutional neural network (CNN) Universal Deep Beamformer (DeepBF) probe Rx Sub-sampling pattern 2x Sub-sampling pattern 4x
- 6. Review : Adaptive Beamforming It is difficult to calculate the inverse of covariance matrix R
- 7. Review : Deconvolution y : RF vector at the depth n H : Deconvolution filter matrices W : Beamformer weight U : [𝒚𝒚 𝒏𝒏 + 𝑸𝑸 𝑻𝑻 … 𝒚𝒚 𝒏𝒏 − 𝑸𝑸 𝑻𝑻 ] 𝑻𝑻 : Deconvolution filter Input dependent non-linear mapping Input dependent Point Spread Function (PSF)
- 8. CNN as a combinatorial representation Encoder-decoder CNN analysis basis synthesis basis Encoder Decoder Similarity between two equation implies that the deconvolution beamforming can be learned using an encoder-decoder CNN. <J. C. Ye and W. K. Sung, “Understanding geometry of encoder-decoder CNNs,” in Proceedings of the 36th International Conference on Machine Learning, >
- 9. Application to Planar Wave Imaging Proposed Method Data Generation Rx Depth Planewave1 Time of flight Planewave2 Planewave3 Planewave
- 10. Results (Planewave / in-vivo) <Full data> 31 plane waves and 64 channels 3 plane waves and 64 channels 31 plane waves and 32 channels 31 plane waves and 8 channels DAS DeepBF 255 128 0 Lateral length(mm) 0 40 30 20 10 depth(mm) 50 0 20 30 40 10
- 11. Results (Planewave / phantom) <Full data> 31 plane waves and 64 channels 11 plane waves and 64 channels 3 plane waves and 64 channels 31 plane waves and 32 channels 31 plane waves and 16 channels 31 plane waves and 8 channels 255 128 0 DAS DeepBF depth(mm) 60 0 24 36 48 12 Lateral length(mm) 0 40 30 20 10 Note that those images are generated from one network.
- 12. Conclusion • The proposed method exploits the redundancies in the raw RF data. • The proposed method can be applied to low-power US, hand-held systems, etc • The proposed universal DeepBF exhibits superior image quality for all sub-sampling rates.
- 13. Thank You