Difference between revisions of "Ultrasound High Speed Microbubble Tracking"
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As a starting point, a simulation script and previously captured raw data is available from the previous project to track air bubbles. | As a starting point, a simulation script and previously captured raw data is available from the previous project to track air bubbles. | ||
The student tasks are: | The student tasks are: | ||
| − | + | * Update the current system to be able to detect Microbubbles (this may requires to modify the imaging method used by the system) | |
| − | + | * Build a measurement setup using commerically microbubbles | |
| − | + | * Engineer the required singal processing algorithms to detect an track the bubbles. | |
===Status: Available === | ===Status: Available === | ||
Revision as of 13:29, 1 August 2018
Short Description
Tracking individual microbubbles injected into the blood flow allows to map capillary systems to a resolution far beyond the limits of conventional imaging. This new disruptive technique is called Ultrafast Ultrasound Localization Microscopy (uULM) link.
However, this technique requires vast amount of processing as several thousand ultrasound images need to be captured at a rate of several kHz and processed. Thus this technique has been mainly applied to 2D imaging only and has only been demonstrated with large research ultrasound system.
With the LightProbe developped at IIS we can implement this modality with much lower cost and hardware requirements. The LightProbe is a handheld ultrasound probe that allows to capture raw ultasound sensor data at a very high rate (>10Gbit/s) and transfer the raw data over a fiber optical link to a GPU equipped PC for processing.
In a first project, we successfully managed to demonstrate detection and tracking of air bubbles at an imaging rate of 200fps.
In this follow up project, we want to switch from air to microbubbles to be able to resolve even finer structures.
This semester/master thesis focuses on the ultrafast tracking of microbubbles in 2D. As a starting point, a simulation script and previously captured raw data is available from the previous project to track air bubbles. The student tasks are:
- Update the current system to be able to detect Microbubbles (this may requires to modify the imaging method used by the system)
- Build a measurement setup using commerically microbubbles
- Engineer the required singal processing algorithms to detect an track the bubbles.
Status: Available
- Looking for Interested Students
- Supervision: Pascal Hager
Character
- 40% Theory & Implementing Algorithms/Signal Processing
- 30% Simulation
- 30% Measurements
Prerequisites
- Knowledge of Matlab
