Supervised machine learning-based classification scheme to segment the brainstem on MRI in multicenter brain tumor treatment context.
Journal:
International journal of computer assisted radiology and surgery
Published Date:
Jan 1, 2016
Abstract
PURPOSE: To constrain the risk of severe toxicity in radiotherapy and radiosurgery, precise volume delineation of organs at risk is required. This task is still manually performed, which is time-consuming and prone to observer variability. To address these issues, and as alternative to atlas-based segmentation methods, machine learning techniques, such as support vector machines (SVM), have been recently presented to segment subcortical structures on magnetic resonance images (MRI).