SpectralHealth

SpectralHealth aims to develop and assess the capability of Hyperspectral Imaging (HSI) for diagnostic and monitoring applications in healthcare. The project will adapt HSI technologies for healthcare as well as develop machine learning (ML) pipelines and visualisation methods for processing of and decision-making on HSI data. It will leverage the development of reusable and interoperable ML-driven solutions by supporting harmonisation of data formats and standardisation of interfaces. The HSI technologies will be validated in five different use cases, each representing major challenges in healthcare where HSI can be harnessed in innovative ways: Surgery – Distinguishing various tissue constituents like nerves, blood vessels, benign and cancerous tissue, etc. by means of HSI and visualisinge by advanced AR technologies; Comorbidities of Diabetes – Monitoring leg perfusion (diabetic foot), faeces (colon cancer), hypoglycaemia, and hypertension improving diabetics’ quality of life and avoid hospitalisation; Dermatology – Monitoring chronic skin conditions such as psoriasis, eczema and skin cancers, and hydration for early detection of melanoma or other adverse skin conditions; Surgical tool inspection – Automatically inspecting surgical instruments for contamination, debris, wear, chemical changes or other damage to ensure safe use during surgery, make cleaning more efficient, and indicate need for replacement; Microbiology – Detecting microbial contamination in unfilterable matrices in high throughput to reduce cycle times for new product modalities and modernize current microbial testing. The potential impact of the project results on healthcare in general and reduction of healthcare costs for society is huge. With an ageing population improving the efficiency of healthcare is mandatory to keep costs in check. Applying HSI solutions can prove to be a disruptive factor by providing innovative and more efficient tools for care professionals in clinical settings