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

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Yu, Peicong, Sheah, Kenneth, Poh, Chueh Loo
Other Authors: School of Chemical and Biomedical Engineering
Format: Article
Language:English
Published: 2013
Online Access:https://hdl.handle.net/10356/97445
http://hdl.handle.net/10220/13150
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-97445
record_format dspace
spelling sg-ntu-dr.10356-974452020-03-07T11:35:37Z Automating the tracking of lymph nodes in follow-up studies of thoracic CT images Yu, Peicong Sheah, Kenneth Poh, Chueh Loo School of Chemical and Biomedical Engineering 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. 2013-08-16T03:46:37Z 2019-12-06T19:42:51Z 2013-08-16T03:46:37Z 2019-12-06T19:42:51Z 2012 2012 Journal Article Yu, P., Sheah, K.,& Poh, C. L. (2012). Automating the tracking of lymph nodes in follow-up studies of thoracic CT images. Computer Methods and Programs in Biomedicine, 106(3), 150-159. 0169-2607 https://hdl.handle.net/10356/97445 http://hdl.handle.net/10220/13150 10.1016/j.cmpb.2010.09.003 en Computer methods and programs in biomedicine
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
description 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.
author2 School of Chemical and Biomedical Engineering
author_facet School of Chemical and Biomedical Engineering
Yu, Peicong
Sheah, Kenneth
Poh, Chueh Loo
format Article
author Yu, Peicong
Sheah, Kenneth
Poh, Chueh Loo
spellingShingle Yu, Peicong
Sheah, Kenneth
Poh, Chueh Loo
Automating the tracking of lymph nodes in follow-up studies of thoracic CT images
author_sort Yu, Peicong
title Automating the tracking of lymph nodes in follow-up studies of thoracic CT images
title_short Automating the tracking of lymph nodes in follow-up studies of thoracic CT images
title_full Automating the tracking of lymph nodes in follow-up studies of thoracic CT images
title_fullStr Automating the tracking of lymph nodes in follow-up studies of thoracic CT images
title_full_unstemmed Automating the tracking of lymph nodes in follow-up studies of thoracic CT images
title_sort automating the tracking of lymph nodes in follow-up studies of thoracic ct images
publishDate 2013
url https://hdl.handle.net/10356/97445
http://hdl.handle.net/10220/13150
_version_ 1681042519352147968