About the project
Minimally invasive surgery (MIS), with laparoscopy as the gold standard in gynecology, offers a gentle method of examination and treatment of the abdominal cavity and the female reproductive organs. Nevertheless, recurrences and repeat surgeries occur time and again due to tissue that has not been removed or has been incompletely removed.
This project focuses on algorithms for tissue analysis using spectral imaging sensors in MIC, with an emphasis on the diagnosis of endometriosis.
By analyzing self-acquired image data, characteristic features are identified to differentiate human tissue. Classification methods (machine learning) are applied and optimized using nonlinear modeling and synthetic extensions.