EPSRC - CLIRPath-AI: Integrating infrared spectroscopy and digital pathology: an explainable AI multi-modal framework for breast cancer diagnosis

Cancer diagnosis currently relies mostly on imaging and tissue analysis, which can make the process prone to errors due to the subjective interpretation of the pathologists. Our project proposes a combined approach (based on multi-modal AI) that integrates histopathological images (detailed pictures of tissue samples) with infrared spectroscopy (a technology that looks at the chemical properties of tissues) to provide comprehensive insights into tumour progression.

The proposed approach has the potential to (i) enhance the accuracy and reliability of cancer diagnosis by leveraging the strengths of both data modalities and (ii) complement the morphological details obtained from histopathological images with molecular spectroscopy information (i.e., information about the parts that make up the tissue).