Anatomical Feature Segmentation of Femur Point Cloud Based on Medical Semantics  

作　　者：Xiaozhong Chen 

机构地区：[1]School of Intelligent Manufacturing,Changzhou Vocational Institute of Engineering,Changzhou,213164,China

出　　处：《Molecular & Cellular Biomechanics》2023年第1期1-14,共14页分子与细胞生物力学（英文）

基　　金：Changzhou Science and Technology Support Plan Project(Grant No.CE20205006);the Qing Lan Project of Jiangsu Province(Grant No.2022CZIE);the Key Project of Educational Science in Jiangsu Province(Grant No.B/2021/03/37).

摘　　要：Feature segmentation is an essential phase for geometric modeling and shape processing in anatomical study of human skeleton and clinical digital treatment of orthopedics.Due to various degrees of freedom of bone surface,the existing segmentation algorithms can hardly meet specific medical need.To address this,a novel segmentation methodology for anatomical features of femur model based on medical semantics is put forward.First,anatomical reference objects(ARO)are created to represent typical characteristics of femur anatomy by 3D point fitting in combination with medical priori knowledge.Then,local point clouds between adjacent anatomies are selected according to the AROs to extract boundary feature point(BFP)s.Finally,the complete model of femur is divided into anatomical regions by executing the enhanced watershed algorithm guided with BFPs.Experimental results show that the proposed method has the advantages of automatic segmentation of femoral head,neck and other complex areas,and the segmentation results have better medical semantics.In addition,the slight modification of segmentation results can be achieved by adjusting a few threshold parameter values,which improves the convenience of modification for ordinary users.

关 键 词：Feature segmentation anatomical reference object femur model boundary feature point medical semantics 

分 类 号：R318[医药卫生—生物医学工程] R322[医药卫生—基础医学]