Automatic lung nodule matching for the follow-up in temporal chest CT scans

Helen Hong; Jeongjin Lee; Yeong Gil Shin

doi:10.1117/12.653359

10 March 2006 Automatic lung nodule matching for the follow-up in temporal chest CT scans

Helen Hong, Jeongjin Lee, Yeong Gil Shin

Proceedings Volume 6144, Medical Imaging 2006: Image Processing; 61442T (2006) https://doi.org/10.1117/12.653359
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

We propose a fast and robust registration method for matching lung nodules of temporal chest CT scans. Our method is composed of four stages. First, the lungs are extracted from chest CT scans by the automatic segmentation method. Second, the gross translational mismatch is corrected by the optimal cube registration. This initial registration does not require extracting any anatomical landmarks. Third, initial alignment is step by step refined by the iterative surface registration. To evaluate the distance measure between surface boundary points, a 3D distance map is generated by the narrow-band distance propagation, which drives fast and robust convergence to the optimal location. Fourth, nodule correspondences are established by the pairs with the smallest Euclidean distances. The results of pulmonary nodule alignment of twenty patients are reported on a per-center-of mass point basis using the average Euclidean distance (AED) error between corresponding nodules of initial and follow-up scans. The average AED error of twenty patients is significantly reduced to 4.7mm from 30.0mm by our registration. Experimental results show that our registration method aligns the lung nodules much faster than the conventional ones using a distance measure. Accurate and fast result of our method would be more useful for the radiologist's evaluation of pulmonary nodules on chest CT scans.

Citation Download Citation

Helen Hong, Jeongjin Lee, and Yeong Gil Shin "Automatic lung nodule matching for the follow-up in temporal chest CT scans", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61442T (10 March 2006); https://doi.org/10.1117/12.653359

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