CBCT auto-calibration by contour registration

Susanne Maur; Dzmitry Stsepankou; Jürgen Hesser

doi:10.1117/12.2512181

1 March 2019 CBCT auto-calibration by contour registration

Susanne Maur, Dzmitry Stsepankou, Jürgen Hesser

Proceedings Volume 10948, Medical Imaging 2019: Physics of Medical Imaging; 109481N (2019) https://doi.org/10.1117/12.2512181
Event: SPIE Medical Imaging, 2019, San Diego, California, United States

Abstract

This paper discusses a novel strategy for estimating projection matrices using the contours of anatomical structures tracked on x-ray projection images. It establishes an auto-calibration routine which calculates the geometrical projection parameters from unknown patient geometry based on iterative reconstruction and registration. By introducing the uncertainty of calibration parameters in registration, we achieve a robust correction for broad types of patient motion. As our method does not rely on consistency between projection data and tomography reconstruction it is robust towards truncation, noise and other typical artifacts of CBCT reconstruction. We evaluated our proposed method of auto-calibration on digital reconstructed radiographs (DRRs) of a CT headscan. In a standard dental CBCT setup our approach shows an average recovery of volume sharpness of 83:67% for different motion types.

Citation Download Citation

Susanne Maur, Dzmitry Stsepankou, and Jürgen Hesser "CBCT auto-calibration by contour registration", Proc. SPIE 10948, Medical Imaging 2019: Physics of Medical Imaging, 109481N (1 March 2019); https://doi.org/10.1117/12.2512181

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