Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login 
  • Users Online: 245
  • Home
  • Print this page
  • Email this page
Year : 2022  |  Volume : 8  |  Issue : 1  |  Page : 16

Digital anatomical study based on Chinese Visible Human data sets

Department of Digital Medicine, College of Biomedical Engineering and Medical Imaging, Third Military Medical University (Army Medical University), Chongqing, People's Republic of China

Correspondence Address:
Yi Wu
Institute of Digital Medicine, Biomedical Engineering College, Third Military Medical University (Army Medical University), Gaotanyan Street, Chongqing 400038
People's Republic of China
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/digm.digm_45_21

Rights and Permissions

Chinese Visible Human (CVH) data sets have been widely used in anatomical teaching and scientific research. Based on true-color, thin-thickness, and high-resolution images which are much more superior than computed tomography, magnetic resonance imaging, and ultrasound, human organs have been segmented and three-dimensional (3D) reconstructed, and the organs have higher accuracy and more detailed information, which makes complex anatomical structures simplified, and makes abstract anatomical structure visualization. Through CVH and their 3D models, researchers got much more anatomical new finding and understanding about human anatomy, which can update anatomical reference books and atlas, and can provide more human morphological information for medical students, surgeons, and anatomists. Here, we will provide a brief summary of the CVH data sets and its applications in teaching and research in recent years.

Print this article     Email this article
 Next article
 Previous article
 Table of Contents

 Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
 Citation Manager
 Access Statistics
 Reader Comments
 Email Alert *
 Add to My List *
 * Requires registration (Free)

 Article Access Statistics
    PDF Downloaded104    
    Comments [Add]    

Recommend this journal