Automatic knee cartilage delineation using inheritable segmentation

Sebastian P. M. Dries M.D.; Vladimir Pekar; Daniel Bystrov; Harald S. Heese; Thomas Blaffert; Clemens Bos; Arianne M. C. van Muiswinkel

doi:10.1117/12.769189

11 March 2008 Automatic knee cartilage delineation using inheritable segmentation

Sebastian P. M. Dries M.D., Vladimir Pekar, Daniel Bystrov, Harald S. Heese, Thomas Blaffert, Clemens Bos, Arianne M. C. van Muiswinkel

Author Affiliations +

Proceedings Volume 6914, Medical Imaging 2008: Image Processing; 691439 (2008) https://doi.org/10.1117/12.769189
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

We present a fully automatic method for segmentation of knee joint cartilage from fat suppressed MRI. The method first applies 3-D model-based segmentation technology, which allows to reliably segment the femur, patella, and tibia by iterative adaptation of the model according to image gradients. Thin plate spline interpolation is used in the next step to position deformable cartilage models for each of the three bones with reference to the segmented bone models. After initialization, the cartilage models are fine adjusted by automatic iterative adaptation to image data based on gray value gradients. The method has been validated on a collection of 8 (3 left, 5 right) fat suppressed datasets and demonstrated the sensitivity of 83±6% compared to manual segmentation on a per voxel basis as primary endpoint. Gross cartilage volume measurement yielded an average error of 9±7% as secondary endpoint. For cartilage being a thin structure, already small deviations in distance result in large errors on a per voxel basis, rendering the primary endpoint a hard criterion.

Citation Download Citation

Sebastian P. M. Dries M.D., Vladimir Pekar, Daniel Bystrov, Harald S. Heese, Thomas Blaffert, Clemens Bos, and Arianne M. C. van Muiswinkel "Automatic knee cartilage delineation using inheritable segmentation", Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 691439 (11 March 2008); https://doi.org/10.1117/12.769189

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