Super-resolution imaging project

Project work: Monday, May 29, 13.00-17.00; Tuesday, May 30, 08.00-12.00 and 13.00-17.00; Wednesday, May 31, 13.00-17.00 in the group rooms Building 349, Ground floor Project presentation preparation is Thursday from 8:00-12:00, and the presentations are from 13:00-17:00.

Purpose

The purpose of this project is to get familiar with nonlinear imaging. Data acquisition from a 3D printed micro-flow phantom with microbubbles, and making super-resolution images from the acquired data. The students will have to acquire the data for their own project, and then process the data using a simple super-resolution processing.

Data and parameters

Data location in Dropbox: /CFU_summer_school_2023/assignments/SRI/

 The variables stored in the env_bf.mat file has following descriptions:
 - env: envelope of beamformed data in uint8 format (0~255)
	- [Nz, Nx, Nt] = size(env); % Nz: number of pixels in z-dir, 
	                            % Nx: number of pixels in x-dir, 
	                            % Nt: number of frames
 - metadata
	- metadata.x_axis: x values of the beamforming grid (m) - [Nx, 1] vector
	- metadata.z_axis: z values of the beamforming grid (m) - [1, Nz] vector
	- metadata.frame_rate: frame rate of the imaging system (Hz)
	- metadata.f0:     center frequency (MHz)
	- metadata.dynamic_range: actual dynamic range of env

% If your system has a low memory try the batch compressed data 
% and load a fraction of frames

Project description

Part I: Data generation:

1. Have the syringe flow pump on with a flow rate of 0.12 uL/s.
2. Compare the linear and nonlinear sequences. How does the MBs lookalike in the nonlinear sequence? What is the dynamic range?
3. Change the transmit voltage and investigate the effect of having higher or lower MI on the nonlinear imaging?
4. Change the flow rate or use a different concentration syringe. How sparse are the MBs?
5. When you are satisfied with the setup. Start acquisition and acquire about 3 minutes of data.
6. Later, you will receive an envelope of beamformed data on your USB disk.

Part II: Data processing:

1. Load the envelope data from your own acquired data in Part I or pre-acquired data from a rat kidney.
2. Apply threshold or spatio-temporal filter to enhance MB signal and reduce the background noise.
3. Localize MBs.
4. Insert localizations in a high-resolution image.
5. Try to track MBs using a simple tracker (optional).
6. Insert track positions into a high-resolution image (optional).

Dissemination:

Make a 10 minutes presentation of your project, which will be discussed on Thursday, June 1 from 13:00. There is 15 minutes available for each project group.