The Signal Processing & Data Inference team interprets these data, extracting clinically-meaningful information and presenting it in the most effective manner to the clinicians.
The Proteus team develops novel optical imaging platforms using a range of detectors. Whether used alone, or in conjunction with our bespoke SmartProbes, these platforms generate vast amounts of data from a range of biological models.
To date, the Signal Processing & Data Inference team has concentrated its efforts into data pre-processing (reconstructing and enhancing the raw data) as well as post-processing approaches (extracting clinically valuable information from the pre-processed data). In particular, areas of interest include (but are not limited to):
The amount of data generated on our custom imaging platforms require effective data compression approaches in order to enable real-time operation. This is especially needed for imaging modes where variations of emitted light across the electromagnetic spectrum, as well as fluorescence variation over time, is recorded for each image coordinate.
Restoration algorithms can compensate for a range of fibre, optics and detector artefacts (see figures below). Well recognised artifacts include:
- Inter-core coupling: where light spreads from a core to its neighbours within a multi-core fibre bundle, resulting in blurring of the imaged scene and consequently reduction of the sensing performance of the device.
- Optical blur: where limited magnification capabilities of the optics within the device result in further blurring of the imaged scene.
- Irregular sampling: where the irregular distribution and optical properties of fibre cores within the multi-core fibre bundle result in an undesired honeycomb pattern projected in the imaging sensor.