Optimum Template Selection and Level Set Atlas-based Segmentation
Xijuan Guo · Jisuanji fangzhen · 2009
Current atlas-based segmentation methods can decrease the computation time.However this is not yet sufficient to guarantee the desired quality of segmentation for the most demanding applications.A method of optimum template selection and level set atlas-based segmentation is proposed.On the one hand,the method automatically chooses the 'best'template based on normalized mutual information,and on the other hand,additional constraints are included in these types of intensity-based registration algorithms.These constraints should improve the smoothness of the contours while introducing more local a priori information such as the intensity distribution or the admissible shapes of objects to be segmented.The example is presented to show the superior performance of the proposed thresholding algorithm compared to that of the existing algorithms of the atlas-based segnentation.