Welcome Hanlin to the Biophotonics group!

Hanlin's project is titled 'Deep Learning-Assisted Classification in Raman Spectroscopy for Rapid Detection of Medical Diagnosis'. It aims to enhance the accuracy and speed of medical diagnosis through the development of deep learning-assisted classification methods in Raman spectroscopy. By collecting Raman spectra from both cancerous and non-cancerous tissues, the research focuses on detecting cancers such as brain and prostate cancer. Chemometric analysis is employed to preprocess and analyse the spectral data, enabling differentiation of tissue types. The study incorporates advanced preprocessing techniques to handle spectral noise and variability, ensuring the robustness and reliability of the models. The ultimate goal is to create a rapid, non-invasive diagnostic tool that aids clinicians in making precise and timely decisions, thus protecting human health and reducing patient suffering.