Open AccessNEURAL NETWORK-BASED REPAIRING SKULL DEFECTS: AN INITIAL ASSESSMENT OF PERFORMANCE AND FEASIBILITY
Author(s) -
Quan Zhang,
Yawen Xu,
Jingyu Zhou,
Bo Peng,
Qianyu Zhang,
Wu Jia
Publication year - 2021
Publication title -
journal of mechanics in medicine and biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.236
H-Index - 30
eISSN - 1793-6810
pISSN - 0219-5194
DOI - 10.1142/s0219519421400121
Subject(s) - skull , convolutional neural network , computer science , hausdorff distance , artificial intelligence , segmentation , data set , process (computing) , similarity (geometry) , artificial neural network , convolution (computer science) , set (abstract data type) , computer vision , pattern recognition (psychology) , image (mathematics) , anatomy , biology , programming language , operating system
Accurate 3D reconstruction of the defective part is critically important for repairing defects in the human skull. After investigating the feasibility of 3D convolution neural network (CNN)-based approach, DeepMedic CNN is chosen for repairing defects of the human skull. Training set of 3D CNN model is produced by randomly segmenting the initial 3D model of the skull which come from a whole CT scan of a healthy person. The 3D CNN model was evaluated using a computer-simulated 3D skull model containing the defective part, and in vivo patient. The results showed that based on 160 groups of computer-simulated 3D CT data, the average dice similarity coefficient (DSC), sensitivity (SE) and Hausdorff distance (HD) are 89.31%, 91.81%, and 25.9%, respectively. These quantitative indexes showed that the proposed method is able to do a reliable bone structure predication. For in vivo patient, the obtained model is also able to generate a suitable 3D bone model for the data under consideration. This approach could increase the computational efficiency of the repairing process without the need for segmentation and reconstruction of the skull, and thereby has potential applications to motivating further accurate repairing of defects of skull.