关键词: 曲线聚类, 动力学特征, 感兴趣区域提取, 动态PET影像

Abstract: Concerning the problem that many current clustering methods based on kinetic characteristics ignore the continuous temporal information of Time Activity Curve (TAC), a method for Region Of Interest (ROI) extraction based on curve clustering was proposed in the paper. The proposed method contains three steps. Firstly, K-Means algorithm was used to remove the background to obtain a coarse mask of the heart. Secondly, curve clustering was used to extract myocardium from the heart obtained in the first step. Finally, blood cavity was delineated based on spatial relationship between pixels. The method was applied to extract the ROI from fourteen mouse PET images. The experimental results indicate that the proposed method is more accurate in delineating blood cavity of the fourteen mice than K-Means and Hybrid Clustering Method (HCM), and it is more precise and stable.

Key words: curve clustering, kinetic characteristic, Region Of Interest (ROI) extraction, dynamic PET image