Smart point landmark distribution for thin-plate splines

John Peter Lewis; Hea-Juen Hwang; Ulrich Neumann; Reyes Enciso

doi:10.1117/12.535936

12 May 2004 Smart point landmark distribution for thin-plate splines

John Peter Lewis, Hea-Juen Hwang, Ulrich Neumann, Reyes Enciso

Proceedings Volume 5370, Medical Imaging 2004: Image Processing; (2004) https://doi.org/10.1117/12.535936
Event: Medical Imaging 2004, 2004, San Diego, California, United States

Abstract

Landmark placement is crucial in manual demarcation and registration of anatomical structures, registration of different image modalities (i.e. MRI/CT), labeling training data for lip and face principal component models, training for neural networks, and signal interpolation to name some applications. Although landmark placement at curvature and coordinate extrema (e.g. corners of the mouth, lowest point on the lower lip) is fairly unambiguous, the placement of point landmarks along a linear contour is subjective. Unfortunately the user's choice of landmark placement determines the quality of the resulting registration. In this paper, we present an algorithm to remove these undesired degrees of freedom by re-placing landmarks along the contour. Ambiguous landmarks are moved so as to minimize a thin plate spline energy while constraining the landmarks to the originally specified contour. The resulting landmark placement results in a smoother registration while still interpolating the contours and fixed landmarks. The results show that the ambiguity of manual landmark placement along contours does affect the smoothness of the interpolated registration, and that significantly smoother interpolations can be achieved using our approach. This procedure may also benefit other applications employing landmarks by eliminating unintended curvature (variation) from the landmark data.

Citation Download Citation

John Peter Lewis, Hea-Juen Hwang, Ulrich Neumann, and Reyes Enciso "Smart point landmark distribution for thin-plate splines", Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); https://doi.org/10.1117/12.535936

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