Image segmentation using local shape and gray-level appearance models

Dieter Seghers D.D.S.; Dirk Loeckx; Frederik Maes; Paul Suetens

doi:10.1117/12.648404

8 March 2006 Image segmentation using local shape and gray-level appearance models

Dieter Seghers D.D.S., Dirk Loeckx, Frederik Maes, Paul Suetens

Proceedings Volume 6144, Medical Imaging 2006: Image Processing; 614401 (2006) https://doi.org/10.1117/12.648404
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

A new generic model-based segmentation scheme is presented, which can be trained from examples akin to the Active Shape Model (ASM) approach in order to acquire knowledge about the shape to be segmented and about the gray-level appearance of the object in the image. Because in the ASM approach the intensity and shape models are typically applied alternately during optimizing as first an optimal target location is selected for each landmark separately based on local gray-level appearance information only to which the shape model is fitted subsequently, the ASM may be misled in case of wrongly selected landmark locations. Instead, the proposed approach optimizes for shape and intensity characteristics simultaneously. Local gray-level appearance information at the landmark points extracted from feature images is used to automatically detect a number of plausible candidate locations for each landmark. The shape information is described by multiple landmark-specific statistical models that capture local dependencies between adjacent landmarks on the shape. The shape and intensity models are combined in a single cost function that is optimized non-iteratively using dynamic programming which allows to find the optimal landmark positions using combined shape and intensity information, without the need for initialization.

Citation Download Citation

Dieter Seghers D.D.S., Dirk Loeckx, Frederik Maes, and Paul Suetens "Image segmentation using local shape and gray-level appearance models", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 614401 (8 March 2006); https://doi.org/10.1117/12.648404

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