Intraoperative Brain Tumor Detection Using Raman Spectroscopy Data and Machine Learning

This project aims to improve brain tumor detection during surgery using Raman spectroscopy and machine learning. Gliomas are a common type of brain tumour that affects survival rates. By analysing tissue spectra with mathematical and statistical methods, a significant spectral difference at 1460 cm-1 was found between healthy and tumour tissue. The programme can tell healthy brain tissue from tumour tissue with 89% accuracy and identify tumours with over 96% accuracy. This makes tumour removal safer and more effective.