Automating the tracking of lymph nodes in follow-up studies of thoracic CT images

Abstract

The study of lymph node features over time is of great clinical significance. Tracking of the same lymph node in CT images over time is done manually in the current clinical practice, which is tedious and lack of consistency. In this paper, we propose a search scheme to automate the process. Regions of interest (ROIs) are located by mapping the center point of lymph node based on the transformation found in the rigid registration. Similarity values between ROI of the template image and ROIs of repository images are compared, the highest of which decides the best match. Our method generated a success rate of 82% in determining the corresponding image in follow-up scan with the same lymph node as in baseline. The location of the lymph node in the corresponding image is tracked and estimated by mapping the lymph node center at baseline image using the transformation obtained from both affine and free-form deformation (FFD) registration. FFD performs better than affine registration in tracking the lymph node location. All lymph nodes in our study are tracked successfully by the suggested points which fall within the boundary of the same node in the corresponding follow-up images using FFD registration.