Accuracy and reliability of a fully automated landmark identification system on Cone Beam Computed Tomography

ABSTRACT Introduction: Medical imaging continues to play an increasing role in health care and is an integral part of medicine and dentistry. Recent technological advancements have led to the development of fully automated landmark identification (ALI) systems capable of tracing Cone-Beam Computed T...

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Main Authors: Ghowsi, Ali, Hatcher, David, Suh, Heeyeon, Park, Joorok, Oh, Heesoo
Format: Others
Published: Scholarly Commons 2021
Subjects:
Online Access:https://scholarlycommons.pacific.edu/dugoni_etd/17
https://scholarlycommons.pacific.edu/cgi/viewcontent.cgi?article=1019&context=dugoni_etd
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spelling ndltd-pacific.edu-oai-scholarlycommons.pacific.edu-dugoni_etd-10192021-10-02T17:11:56Z Accuracy and reliability of a fully automated landmark identification system on Cone Beam Computed Tomography Ghowsi, Ali Hatcher, David Suh, Heeyeon Park, Joorok Oh, Heesoo ABSTRACT Introduction: Medical imaging continues to play an increasing role in health care and is an integral part of medicine and dentistry. Recent technological advancements have led to the development of fully automated landmark identification (ALI) systems capable of tracing Cone-Beam Computed Tomography (CBCT). The purpose of this study was to evaluate the accuracy and reliability of an ALI system as a tool for automatic landmark location compared to human judges. Methods: One hundred subjects’ CBCT volumes from multiple imaging centers were traced by two human judges who were calibrated and had an ICC close to 1. Fifty-three landmarks were identified in the x, y, and z coordinate planes using Checkpoint Software (Stratovan Corporation, Davis, CA). The ground truth was created by calculating the mean values of the x, y, and z coordinates for each landmark across both judges’ landmark identification. To evaluate the accuracy of ALI, the mean absolute error at each coordinate and mean error distance (mm) between the human landmark identification (ground truth) and the ALI were determined, and a successful detection rate (SDR) was calculated. Results: Overall, the ALI system was as successful at landmarking as the human judges with the exception of a few landmarks. The mean error distance for all 53 landmarks was 4.04 mm ± 6.5. Forty-nine out of 53 landmarks were located within a mean error of 4mm when the average for the coordinates of human judges was considered as a ground truth. Conclusion: Across all three coordinate planes, 96% of the landmarks had a mean absolute error of less than 4mm when compared to the ground truth. The ALI was more precise than humans when identifying landmarks on the same image at different times. This study demonstrates the promise of ALI in aiding orthodontists with landmark identification on CBCTs in the future. 2021-01-01T08:00:00Z text application/pdf https://scholarlycommons.pacific.edu/dugoni_etd/17 https://scholarlycommons.pacific.edu/cgi/viewcontent.cgi?article=1019&context=dugoni_etd Orthodontics and Endodontics Theses Scholarly Commons Automated Landmark Accuracy Reliability CBCT Dentistry Endodontics and Endodontology Orthodontics and Orthodontology
collection NDLTD
format Others
sources NDLTD
topic Automated Landmark
Accuracy
Reliability
CBCT
Dentistry
Endodontics and Endodontology
Orthodontics and Orthodontology
spellingShingle Automated Landmark
Accuracy
Reliability
CBCT
Dentistry
Endodontics and Endodontology
Orthodontics and Orthodontology
Ghowsi, Ali
Hatcher, David
Suh, Heeyeon
Park, Joorok
Oh, Heesoo
Accuracy and reliability of a fully automated landmark identification system on Cone Beam Computed Tomography
description ABSTRACT Introduction: Medical imaging continues to play an increasing role in health care and is an integral part of medicine and dentistry. Recent technological advancements have led to the development of fully automated landmark identification (ALI) systems capable of tracing Cone-Beam Computed Tomography (CBCT). The purpose of this study was to evaluate the accuracy and reliability of an ALI system as a tool for automatic landmark location compared to human judges. Methods: One hundred subjects’ CBCT volumes from multiple imaging centers were traced by two human judges who were calibrated and had an ICC close to 1. Fifty-three landmarks were identified in the x, y, and z coordinate planes using Checkpoint Software (Stratovan Corporation, Davis, CA). The ground truth was created by calculating the mean values of the x, y, and z coordinates for each landmark across both judges’ landmark identification. To evaluate the accuracy of ALI, the mean absolute error at each coordinate and mean error distance (mm) between the human landmark identification (ground truth) and the ALI were determined, and a successful detection rate (SDR) was calculated. Results: Overall, the ALI system was as successful at landmarking as the human judges with the exception of a few landmarks. The mean error distance for all 53 landmarks was 4.04 mm ± 6.5. Forty-nine out of 53 landmarks were located within a mean error of 4mm when the average for the coordinates of human judges was considered as a ground truth. Conclusion: Across all three coordinate planes, 96% of the landmarks had a mean absolute error of less than 4mm when compared to the ground truth. The ALI was more precise than humans when identifying landmarks on the same image at different times. This study demonstrates the promise of ALI in aiding orthodontists with landmark identification on CBCTs in the future.
author Ghowsi, Ali
Hatcher, David
Suh, Heeyeon
Park, Joorok
Oh, Heesoo
author_facet Ghowsi, Ali
Hatcher, David
Suh, Heeyeon
Park, Joorok
Oh, Heesoo
author_sort Ghowsi, Ali
title Accuracy and reliability of a fully automated landmark identification system on Cone Beam Computed Tomography
title_short Accuracy and reliability of a fully automated landmark identification system on Cone Beam Computed Tomography
title_full Accuracy and reliability of a fully automated landmark identification system on Cone Beam Computed Tomography
title_fullStr Accuracy and reliability of a fully automated landmark identification system on Cone Beam Computed Tomography
title_full_unstemmed Accuracy and reliability of a fully automated landmark identification system on Cone Beam Computed Tomography
title_sort accuracy and reliability of a fully automated landmark identification system on cone beam computed tomography
publisher Scholarly Commons
publishDate 2021
url https://scholarlycommons.pacific.edu/dugoni_etd/17
https://scholarlycommons.pacific.edu/cgi/viewcontent.cgi?article=1019&context=dugoni_etd
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AT parkjoorok accuracyandreliabilityofafullyautomatedlandmarkidentificationsystemonconebeamcomputedtomography
AT ohheesoo accuracyandreliabilityofafullyautomatedlandmarkidentificationsystemonconebeamcomputedtomography
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