The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Dec. 04, 2018
Filed:
Jun. 14, 2017
The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, CN;
School of Data and Computer Science of Sun Yat-sen University, Guangzhou, Guangdong, CN;
National Supercomputer Centre IN Guangzhou of Sun Yat-sen University, Guangzhou, Guangdong, CN;
Liwei Yan, Guangdong, CN;
Shuang Zhu, Guangdong, CN;
Xiaolin Liu, Guangdong, CN;
Jian Qi, Guangdong, CN;
Qingtang Zhu, Guangdong, CN;
Yao Lu, Guangdong, CN;
Yongze Guo, Guangdong, CN;
Sha Yu, Guangdong, CN;
Yutong Lu, Guangdong, CN;
Xi Zhang, Guangdong, CN;
Yunfei Du, Guangdong, CN;
Tao Lin, Guangdong, CN;
THE FIRST AFFILIATED HOSPITAL OF SUN YAT-SEN UNIVERSITY, Guangzhou, CN;
SCHOOL OF DATA AND COMPUTER SCIENCES OF SUN YAT-SEN UNIVERSITY, Guangzhou, CN;
NATIONAL SUPERCOMPUTER CENTRE IN GUANGZHOU OF SUN YAT-SEN UNIVERSITY, Guangzhou, CN;
Abstract
The present invention relates to fields of clinical application of nerve defect repair and the medical three-dimensional (3D) printing technology, and provides an integrated visualization method for three-dimensional (3D) reconstruction of internal structure of human peripheral nerves. The method comprises the following steps: obtaining human peripheral nerves, preparing nerve specimens ex vivo by staining with an iodine preparation in combination with a freeze-drying method; scanning the pretreated peripheral nerves using Micro CT to acquire lossless two-dimensional images, and performing binarization processing to the two-dimensional images, then conducting image segmentation based on textural features to acquire images of nerve fascicles; finally, reconstructing the segmented images into a visualization model by using a supercomputer.