Difference between revisions of "Compression of Ultrasound data on FPGA"
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Latest revision as of 15:57, 16 September 2022
Wearable Ultrasound probes appear as a promising tool for assisting medical therapies and sport science in the characterization of musculoskeletal features on humans. A typical wearable probe is equipped with a wireless link, which is the main power consumer of the system. To reduce the power consumption of a wearable probe, at the same time guaranteeing high frame rates, compression of the ultrasound data is required. In this project, you will explore alternative compression methods for raw ultrasound data, and you will port the selected algorithms on an FPGA.
Goal & Tasks
The goal of this project is to evaluate compression algorithms to be applied on raw Ultrasound data, ultimately implementing them as RTL modules on an FPGA. The main tasks of this project are:
- Literature study of compression algorithms for ultrasound (lossless and lossy)
- Implementing selected algorithms in Python and evaluating the performance on existing Ultrasound datasets
- Hardware design on a Xilinx Artix-7 FPGA
- Signal processing basics
- Python (numpy, scipy, etc.)
- 20% Literature Study
- 40% Simulations of the compression process
- 40% Implementation on the hardware
NOTE: in view of COVID-19 restrictions, this project can be done 100% remotely