Visualizing the spine using anatomical knowledge

Craig W. Cornelius; Linda L. Fellingham

doi:10.1117/12.19989

1 August 1990 Visualizing the spine using anatomical knowledge

Craig W. Cornelius, Linda L. Fellingham

Proceedings Volume 1259, Extracting Meaning from Complex Data: Processing, Display, Interaction; (1990) https://doi.org/10.1117/12.19989
Event: Electronic Imaging: Advanced Devices and Systems, 1990, Santa Clara, CA, United States

Abstract

In vivo anatomy is now routinely displayed as 2-D and 3-D images obtained from Computed X-ray Tomograpy (CT), Magnetic Resonance Imaging (MRI), and other diagnostic modalities. Most current medical visualization methods rely on pixel intensities to segment the data into tissues. However, structural features must be differentiated by a human operator, and geometric measurements of the anatomy are tedious and error prone to compute. This paper describes processing and imaging methods to aid the interpretation of CT studies of the spine. These procedures incorporate knowledge of the symmetry, shapes, and spatial relationships of vertebrae to locate the spinal cord and major components of vertebral bone from CT slices of the spine and automatically compute anatomical measurements. Results of these methods are shown as applied to the cervical (neck) and lumbar (lower back) regions of the spine.

Citation Download Citation

Craig W. Cornelius and Linda L. Fellingham "Visualizing the spine using anatomical knowledge", Proc. SPIE 1259, Extracting Meaning from Complex Data: Processing, Display, Interaction, (1 August 1990); https://doi.org/10.1117/12.19989

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available