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Project Title:

Smart Sensing for Off-Grid Error Reduction in Compressed Sensing Algorithms

Project ID:

3332

Abstract:

Compressed Sensing is a novel family of algorithms that make use of a sparse structure of the signal to perform an effective recovery. This kind of algorithms make use of a "sensing matrix" to relate the measurements to the original signal. In many cases this sensing matrix is a grid matrix that take a continuous parameter on which the signal depends, such as frequency or angle, and discretizes it. However, in this case, a problem arise when the true parameter from which the signal was generated is "off the grid".

The project goal is to design a smart sensing matrix that reduce the possible implications of the off grid problem.
The project will include research next to matlab and will contain algorithmic aspect.

Description:

File not available

Supervisor(s):
Student(s):
Idan Fried
Project Title:

Cognitive Indoor Localization - Part 2

Project ID:

3562

Abstract:

It is often desired to locate objects or people inside buildings using some identification sensors attached to them such as smartphones. In outdoor environments, persons carrying smartphones can be easily located by GPS satellites. However, the GPS signal loses its strength inside buildings, garages and offices due to signal attenuation caused by construction materials and multipath fading. This challenge has led to active research on various localization techniques for indoor environments.

In this particular project, we plan to use cognitive transmission in IEEE 802.11ad 60 GHz link to enhance the SNR of the received signal and improve range detection. The signal setup comprises of a wireless access point installed indoors that communicates with the smartphones of the users to determine their locations.

Description:

File not available

Supervisor(s):
Student(s):
Monin Sagi & Yona Cohen
Project Title:

Parameter estimation of multiband signals from sub-Nyquist samples

Project ID:

3114

Abstract:

The MWC efficiently samples and reconstructs sparse wideband, or multiband, signals below the Nyquist rate,without a priori knowledge of their support. However, in some applications, the transmissions composing the wideband signal are known to belong to certain function families, such as CW, pulses with known shapes,chirps… The unknown parameters are the carrier frequencies, delays, amplitudes, scaling factors, symbol rates…


In this project, our goal is to incorporate this a priori knowledge and derive a sampling scheme that allows recovering the unknown parameters while reducing the sampling rate and sensing time.

Description:

File not available

Supervisor(s):
Student(s):
Rotem Turjeman & Inbal Fleischer
Project Title:

Image deconvolution In fluorescence microscopy - Part 2

Project ID:

3173

Abstract:

Project description:
Super resolution fluorescence microscopy techniques are an ensemble of light-microscopy techniques which achieve spatial resolution beyond the limitations imposed by the diffraction of light. On the other hand, since its introduction in 1983, deconvolution microscopy has become a key processing tool for the visualization of cellular structures of fixed and living specimens in three dimensions and at sub-resolution scale.

Deconvolution is also referred to as an inverse problem, since given the output of the system we aim at recovering the input to the system.

In the proposed project we will extend deconvolution techniques to image de-blurring in microscopy. We will exploit the sparsity prior in acquired images to improve the results.

Description:

File not available

Supervisor(s):
Student(s):
Irina Akhvlediany
Radar
Project Title:

Sub-Nyquist MIMO Doppler Processing and Clutter Removal

Project ID:

3458

Abstract:

Multiple input multiple output (MIMO) radar is a novel radar paradigm that uses an array of several transmit and receive antenna elements, with each transmitter radiating a different waveform. In a collocated MIMO radar, the antenna elements are placed close to each other so that the radar cross-section of a target appears identical to all the elements. The waveform diversity in a collocated MIMO is based on the mutual orthogonality - usually in time, frequency or code - of different transmitted signals. The receiver separates and coherently processes the target echoes corresponding to each transmitter. The angular resolution of MIMO is same as a virtual phased array with the same antenna aperture but many more antenna elements than MIMO.

Recently, we designed and developed a sub-Nyquist MIMO radar that requires less number of antenna elements and signal samples without degrading the angular and range resolutions of the radar. The objective of this project is to add Doppler processing and clutter removal algorithms to this prototype. We would use existing theoretical solutions to integrate these modules and then validate the results using the hardware prototype in real-time.

Description:

File not available

Supervisor(s):
Student(s):
Eran Ronen & Yana Grimovich
Project Title:

Compressed Channel Estimation for Millimeter Wave MIMO system

Project ID:

3128

Abstract:

In the race toward increasing data rates at cellular networks, mmWave MIMO (Multiple Input Multiple Output) systems are considered a leading candidate for 5G standard, the next generation of cellular technology.
Using mmWave offers multiple advantages, such as channel bandwidths far greater than previously available and larger antenna arrays, but also arouse new difficulties such as expensive RF chains, and massive amount of data need to be processed digitally.
This difficulties raise the need to come up with a new solution that will consider both the analog and digital domains.

To reduce the necessary amount of expensive RF chains we aim to exploit the sparse mmWave channel model.
The goal of the project is to develop a new sensing scheme for the mmWave model along with an algorithm for the channel estimation.
The project will include research next to matlab implementation

Required background: Introduction to Digital Signal Processing (044198)

Description:

File not available

Supervisor(s):
Student(s):
Mordov Shai & Rivka Emanuel
Project Title:

High Spatial Resolution Radar

Project ID:

3197

Abstract:

In Collaboration with: Mafat - המינהל למחקר, פיתוח אמצעי לחימה ותשתית טכנולוגית

Project description:
A radar transmits electromagnetic waves in very short pulses and measures the returned power, time lag and frequency of em waves backscattered from targets as the pulse travels away from the radar. From the properties of the backscattered signal, one may obtain information such as location, velocity and size of the radar target. One of the advanced radar antennas in use today is phased array, which consists of several radiating elements and phase shifters. The radiating beam pattern of a phased array is highly directional and allows for agile scanning of target scene. The spatial resolution is determined by the aperture of the array which determines the number of elements needed to prevent spatial aliasing. The more the number of elements, better would be spatial resolution.

The goal of this project is to break the traditional link between the spatial resolution and the number of elements. We will use time division approach in order to radiate on the targets using a sparse sub-array for each transmission. By fusing all the received data and integrating a new processing algorithm, we would try to achieve a better effective spatial resolution with reduced number of elements.

Supervisor: Kumar Vijay Mishra (mishra@ee.technion.ac.il) and David Cohen (davidcohenys@gmail.com)

Required background: Signal and systems, Mavlas , Random signals (optional)

Environment: Matlab

Description:

File not available

Supervisor(s):
Student(s):
Itay Kahane & Aviad Kaufmann
Project Title:

Two-dimensional Sub-Nyquist SAR demo

Project ID:

3333

Abstract:

Synthetic Aperture Radar (SAR) is a well-proven radar imaging technology that is capable of producing high-resolution images of stationary surface targets and terrain. The main advantages of SAR are its ability to operate at night and in adverse weather conditions, hence overcoming limitations of both optical and infrared systems. The basic idea of a SAR system is to produce a two-dimensional mapping of the illuminated scene from received echoes by processing the reflected energy.
The goal of the project is to implement a full-cycle demo that allows to construct an image from low-rate samples at both fast time and slow time.

Description:

File not available

Supervisor(s):
Student(s):
Ran Ben-Izhak & Beary Fluss
Biomedical
Project Title:

שיטות MRF מתקדמות

Project ID:

3502

Abstract:

הדמיית תהודה מגנטית (MRI) היא השיטה המועדפת לאבחון, הערכה, מעקב וניתוח של פתולוגיות קליניות. יחד עם זאת, רכישה של הדמיית MRI מרובת רצפים היא תהליך איטי יחסית הדורש בממוצע כחצי שעה. MRF הינה שיטה חדשנית המספקות הערכה כמותית של הפרמטרים הפיזיקליים של הרקמות השונות. בפרוייקט זה נממש ונבחן שיטות מתקדמות לשערוך התמונות הכמותיות ונשווה את תוצאותיו לאלגוריתם מבוסס חישה דחוסה (CS). פרויקט כיפי ושאפתני עם אלמנט מחקרי שנועד להכיר לסטודנטים את עולם ה MRI ואת גישת "טביעת האצבע" ((MRF המספקת מדדים פיזיקליים כמותיים של הרקמות. בנוסף הסטודנטים ילמדו ויכירו שיטות עבוד אות המבוססות דגימה דחוסה.

קיימת אפשרות לפרוייקט המשך למעוניינים.

Description:

File not available

Supervisor(s):
Student(s):
Inbal Fleischer | Brian Chmiel
Project Title:

multi-leads ECG compression

Project ID:

3503

Abstract:

The use of ECG signal, which demonstrate the heart's electric activity, is common in many applications. In mobile applications such as pacemakers, there is a significant importance to save battery energy and hence to compress the signal and sub sampled it.

Project description:

In this project, we will continue the work that has been done in the lab for compressing the signal and sub sampling it, and we will realize different medical applications such as pain detector for a patient under the influence of anesthesia. The project is held with cooperation of Sheba hospital and with the assistance of the cardiologist Dr. Shai Tagmen Yarden.An ambitious and fun project, which focuses on introducing the ECG signal and the world of compressed sensing (CS), in the field of signal processing.

There is a possibility for a 2 semester project to those who will be interested.


Description:

File not available

Supervisor(s):
Student(s):
Klein Roi
Project Title:

FDBF for Diverging Wave Imaging

Project ID:

3653

Abstract:

Medical ultrasound is used for tissue visualization by radiating it with acoustic energy transmitted by an array of elements. Novel imaging method based on insonification with diverging improves image quality and acquisition time.

This method, however, is limited by data transfer rates and severe computational load. Therefore, this imaging mode can significantly benefit from coupling with the low-rate frequency domain beamforming approach developed recently in SAMPL.

In this project we aim to adopt frequency domain beamforming framework to diverging wave compounding waves imaging mode. The combination of these two novel techniques will allow for significant reduction in both sampling and processing rates in paving a way to real-time ultrafast processing.

Performance of modified FDBF will be tested on data in Matlab environment.

Description:

File not available

Supervisor(s):
Student(s):
Cohen-Sidon Omer & Aviv Rabinovich
Project Title:

Limited Diffraction-based Imaging

Project ID:

3692

Abstract:

Ultrasound is used for tissue visualization by radiating it with acoustic energy transmitted by an array of elements. Image is derived by integrating the signals received by individual elements. A new novel approach based on limited diffraction beams allows acquiring data directly in k-space and recover the image using inverse Fourier transform leading to improved acquisition time and image quality.

In this project we aim to study and implement the above approach and introduce novel k-space re-sampling technique developed recently at SAMPL.


Description:

File not available

Supervisor(s):
Student(s):
Aviad Aberdam, Eliav Bar-Ilan
Project Title:

Migraine classification via fMRI and EEG

Project ID:

3685

Abstract:

Migraine is a primary headache disorder characterized by recurrent headaches that are moderate to severe. Typically, the headaches affect one half of the head, are pulsating in nature, and last from two to 72 hours.

Functional MRI (fMRI) and EEG may be used to investigate the mechanisms that lead to migraine by measuring functional connectivity. This could provide fMRI and EEG based biomarkers that indicate early responses to preventive therapy. The goal of the project is to identify those biomarkers via acquisition of EEG and fMRI data of both healthy and Migraine diagnosed subjects.

Description:

File not available

Supervisor(s):
Student(s):
Jonathan Yarnitsky, reut azaria
Project Title:

Ultrafast Sub-Nyquist Tissue Doppler Ultrasound System

Project ID:

3135

Abstract:

Tissue Doppler ultrasound imaging (TDI) enables the estimation of cardiac function by transmitting streams of pulses in a certain direction and estimating the velocity of the tissue from the phase shifts of the returning echoes. In order to estimate the velocity of the tissue precisely and separate slow tissue movement from dominant clutter, a large number of pulses has to be transmitted in the same direction. TDI has two main limitations: First, the number of transmitted pulses per unit of time is limited by the speed of sound in tissue and the desired imaging depth, therefore there is an inherent tradeoff between spectral and spatial resolution. This limitation impedes TDI usage to a few measurements through the LV wall. Second, in current systems the echoes detected by transducer elements are sampled at high rates of 3-4 times beyond their Nyquist rate, and processed to create a focused reception along a beam. A recent trend in ultrasound imaging is the transmission of unfocused beams (diverging waves) that enable the simultaneous scan of entire sectors. This shift in paradigm increases the frame rate significantly.Xampling and Compressed Sensing methods developed at SAMPL, allows the reconstruction of signals sampled at a sub-Nyquist rate with reduced number of pulses per velocity estimation, using priors on the sparsity of the signal. This reduced sapling is performed without compromising the same time temporal and spatial resolutions.In this project the implementation of the sub-Nyquist TDI demo system will be extended to include transmission of diverging waves. The system developed in this project will pave the way for quantitative cardiac imaging. In this project you will become familiar with Xampling and Compressed Sensing theory and Matlab simulations. In addition, you will gain experience in implementing signal processing algorithms on real ultrasound systems.

Description:

File not available

Supervisor(s):
Student(s):
Ido Cohen & Shai Yagil
Project Title:

Parallel Imaging MRI

Project ID:

3211

Abstract:

Parallel Imaging MRI

Magnetic Resonance Imaging (MRI) is the method of choice for diagnosis, evaluation and follow-up of brain clinical pathologies. However, the acquisition of a routine brain MRI requires an average of 50 minutes per examination. To deal with this problem, there are in the modern scanners multiple acquisition coils. In each coil, some of the data is acquired partially or sparsely and then the entire image is reconstructed from all the coil based images. In this project we will learn, understand and realize this reconstruction method from data that has been taken from several coils in a real scanner. An ambitious and fun project which focuses on introducing the world of MRI and the popular parallel imaging field combined with compressed sensing (CS) methods, which leads to shorter scan time.
There is a possibility for a 2 semester project to those who will be interested.
For further details, please contact Gal Mazor: galmazor@campus.technion.ac.il

Description:

File not available

Supervisor(s):
Student(s):
Chechik Yonatan
Project Title:

Phase-Coherence for Medical Ultrasound

Project ID:

3221

Abstract:

Medical ultrasound is used for tissue visualization by radiating it with acoustic energy transmitted by an array of elements. The image quality is defined by the parameters of the array beampattern. The resolution is proportional to the main-lobe width and the contrast is defined by the side-lobes level.

In this project we aim to improve the above by applying phase coherence factor (PCF). This approach exploits the phase information at each transducer element to compute a weight factor per each pixel within an image. The factor is nearly one for the signal coming from the focal point and is close to zero for signals originating within the side and grating lobes.

The method will be first applied to real ultrasound data obtained in commercially used focused mode. Next it will be extended and applied to novel coherent phase compounding approach.

Description:

File not available

Supervisor(s):
Student(s):
Dan Cohen and Meged Shoham
Project Title:

Sub-Sampling of Functional CT

Project ID:

3243

Abstract:

Project description:
X-Ray Computer Tomography, known as CT, is one of the main tools Doctors use today to examine patients. In every main hospital, there are CT machines that work 24/7 to provide Doctors with in-depth views of the human body. CT Scans enable them to save lives on a daily basis.

In functional CT methodology the CT constantly acquires new data and updates the scan results. The output is a dynamic image of the human body. Functional CT allows us to view blood flow within the body, analyze dynamic organs, such as the heart, and observe other interesting temporal phenomena.

In this project the students will first study the basics of computer aided tomography, advanced mathematical imaging tools and cutting edge techniques in signal processing for sub-Nyquist sampling.

Today, functional CT isn't used at all in hospitals due to high radiation dosages involved. We will describe the model for functional CT, and design a clever way to sub-sample the scan. Our goal is to reduce radiation dosage and enable a widespread usage for functional CT applications.

• The project is performed in collaboration with researchers and radiologists from RAMBAM.

Description:

File not available

Supervisor(s):
Student(s):
Ben Finkelshtein & Tomer Zeagdone
Project Title:

Sub-Nyquist Ultrasound Doppler Imaging of Vascular Flow - Part 2

Project ID:

3225

Abstract:

Doppler ultrasound is a non-invasive and safe modality that is used for the estimation of blood velocities by transmitting high-frequency sound waves (ultrasound) and analyzing the signals reflected from circulating red blood cells. Doppler scans help diagnose many conditions, including: heart valve defects and congenital heart disease, artery occlusions and aneurysms. Classic Doppler processing methods do not make use of the underlying structure in the reflected signals in order to reduce the sampling rate or improve the estimation quality. Therefore, multitudes of ultrasound measurements are needed in order to produce reliable velocity estimation for each location and around each time point.
In the first part of this project, sparse representations of the ultrasound Doppler signal were investigated along with ways to estimate the velocity field. In the current project, these results will be used in order to define a sub-nyquist sampling and reconstruction framework for blood Doppler signals. Validation will be performed using numerical simulations, phantom scans and real Doppler ultrasound measurements.

Description:
Supervisor(s):
Student(s):
Yotam Lubin & Noa Yehezkel
Project Title:

Fetal ECG

Project ID:

3279

Abstract:

The use of ECG signal, which demonstrate the heart's electric activity, is common in many applications. When sensing the signal of pregnant women, there is a significant importance to separate the maternal ECG from the fetal one. In this project, we will develop new method for this separation based on very popular field of dictionary learning in the world of signal processing. The project is held with cooperation of Sheba hospital and with the assistance of the cardiologist Dr. Shai Tagmen Yarden. An ambitious and fun project, which focuses on introducing the ECG signal and the world of compressed sensing (CS), in the field of signal processing.
There is a possibility for a 2 semester project to those who will be interested.


For further details, please contact Gal Mazor: galmazor@campus.technion.ac.il

Description:

File not available

Supervisor(s):
Student(s):
Omri Berman & Yotam Nizri
Optics
Project Title:

Super-Resolution Structured Illumination Microscopy

Project ID:

3501

Abstract:

Super resolution fluorescence microscopy techniques are an ensemble of light‐microscopy techniques which achieve spatial resolution beyond the limitations imposed by the diffraction of light. However, these techniques are currently limited by low temporal resolution and long acquisition times. Super‐resolution optical fluctuation imaging (SOFI) is a fluorescence microscopy technique enabling sub‐diffraction limit imaging with high temporal resolution by calculating high order statistics of the fluctuating optical signal. Structured illumination microscopy (SIM) also enables sub‐diffraction resolution and rejection of out‐of‐focus light, for leaving specimen, with a fast imaging cycle.

Project description:

In this project, we will investigate an exciting new direction which will lead to a new type SIM, by taking inspiration from communication methods such as spear spectrum and the MWC developed in SAMPL, to enable increased spatial resolution, well below the diffraction limit. Such a microscope can lead to new advances in biological research. The students will get a hands on experience with a research project, combining disciplines in fluorescence microscopy, sparse representations and optimization techniques.

Description:

File not available

Supervisor(s):
Student(s):
Guy Asherov & דמיאן קלירוף
INTERIA Web Design & Development