## ULM Through DL 7(Randomized Validation Set)

In these sets of experiments, we repeated the same procedure described in the previous post with only one difference. So, please see the details in the previous post. The difference is the way that we…

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# Author: usoylu2

## ULM Through DL 7(Randomized Validation Set)

## ULM Through DL 6

## ULM Through DL 5

## ULM Through DL 4

## ULM Through DL 3

## ULM Through DL 2

## ULM Through Deep Learning

## Literature Survey (Non-Learning Based)

## Literature Survey (Learning Based)

## Literature Survey(Intro)

by Ufuk Soylu

In these sets of experiments, we repeated the same procedure described in the previous post with only one difference. So, please see the details in the previous post. The difference is the way that we…

There are many experiments that I have done for transfer learning. In the first phase of training, I repeated the process that I described in the previous post named as “ULM Through DL 5”. In…

After showing that using deep NN for deconvolution of microbubbles is successful as stated in Eldar at al, we would like to move to more realistic case. Until now, we were using our way of…

After successful training in previous, we increased complexity of the problem gradually. NN trained for multiple bubbles in the target scene with constant Gaussian shaped PSF but PSF varies over the training set NN trained…

Next complexity that we can to handle is spatial variance. In ultrasound imaging, PSFs of micro bubbles are spatially varying. In order to model this, we generated the training dataset comprised of 3 sigma values…

After being successful with single micro bubble, then we can make the problem more complex gradually. Next problem that we deal with is that we still assume that PSF of bubbles are in Gaussian shape…

As a first step for training neural network for ULM (Ultrasound Localization Microscopy ), we trained a neural network for a simplified problem. We assume that micro bubbles are in Gaussian shape. We generated a…

Following works can be found in non-learning based ultrasound imaging: 2D array design Gaussian Function Fit Fourier Domain Low Rank Model Lasso for Micro bubble Super resolution Kalman filter for Micro bubble Super resolution 3-D…

Following works can be found in learning based ultrasound imaging context: Shear Wave Imaging CNN for MV(Minimum Variance) Beamforming Approximation Reinforcement Learning Application Despeckle (GAN and CNN) Compressed Sensing (SLA and Plane Wave Imaging) Learning…

This is a literature survey for ultrasound imaging. It is done on arxiv. First paper that I would like to consider is not directly related to ultrasound imaging but it is a tutorial related to…