Automatic segmentation of brain structures for radiotherapy planning

Abstract

In the past few decades unprecedented advances have been made in the field of medical imaging. Various imaging technologies such as Computed Tomography, Magnetic Resonance Imaging, etc. have emerged to assist the visualization of internal structures in the body. These along with the different image processing tools help in diagnosis and detection of diseases. Intensity Modulated Radiation Therapy (IMRT) is a recently developed and highly effective method for destroying cancerous cells with minimal effect on the other body structures of the patient. It relies on accurate delineation of the structures to be irradiated and those to be spared. Currently the delineation is being done manually, which is very time consuming. We have therefore proposed an atlas-based automatic segmentation method which will significantly reduce the interaction time during radiotherapy planning. In this thesis, the main focus is on improving the results obtained by the atlas-based segmentation method. Three methods have been implemented namely CT-MR fusion method, Mesh deformations and Classifier combination method. We have employed two methods for validating the automatically generated results. This is done by comparing the automatic masks and contours with the manual ground truth segmentation. Finally, the different methods have been compared and the feasibility of automatic delineation has been discussed.