Automatisierte Detektion von Tumorgewebe in der Lunge

The intraoperative classification of tumor tissue is a challenge in daily surgical efforts. Time-consuming immediate sectioning of tissue samples and the lack of intraoperative possibilities to check for residual tumor tissue are the main problems. This is why we made a first step towards a fully mobile and automatic detection and classification system of tumor tissue. We showed that you can differentiate between several types of lung cancer and healthy tissue by measuring autoflurorescence spectra and classifying these with principle component analysis (PCA). We realized a stand-alone device for data acquisition and analysis in real-time for surgical purposes.