TY - JOUR
T1 - Development of an automated patient-recognition method for digital chest radiographs using edge-enhanced images
AU - Kondo, Keisuke
AU - Morishita, Junji
AU - Katsuragawa, Shigehiko
AU - Doi, Kunio
PY - 2003/10
Y1 - 2003/10
N2 - It is important that all images in a picture archiving and communication system (PACS) environment should be stored in the correct location, e.g., in the proper patient's folder. However, if patient information, such as identification number or patient name, has been entered incorrectly, the image may be stored in the wrong place. We are developing an automated patient recognition method for chest radiographs based on a template-matching technique to prevent such filing errors. To further improve the performance of our method, we investigated the usefulness of a new automated patient-recognition method based on a template-matching technique by using edge-enhanced and smoothed images. We found that the relationship between the correlation values obtained with and without the edge-enhancement technique tended to provide different criteria for identifying correct or incorrect patients. When we combined the two methods to distinguish the images by a rule-based method, 67.1% of wrongly identified patients in our database could be identified as wrongly identified, without any false warnings for correctly identified patients. We consider that this automated method for patient recognition based on edge-enhanced images would be useful in preventing "wrong" images from being stored in a PACS environment.
AB - It is important that all images in a picture archiving and communication system (PACS) environment should be stored in the correct location, e.g., in the proper patient's folder. However, if patient information, such as identification number or patient name, has been entered incorrectly, the image may be stored in the wrong place. We are developing an automated patient recognition method for chest radiographs based on a template-matching technique to prevent such filing errors. To further improve the performance of our method, we investigated the usefulness of a new automated patient-recognition method based on a template-matching technique by using edge-enhanced and smoothed images. We found that the relationship between the correlation values obtained with and without the edge-enhancement technique tended to provide different criteria for identifying correct or incorrect patients. When we combined the two methods to distinguish the images by a rule-based method, 67.1% of wrongly identified patients in our database could be identified as wrongly identified, without any false warnings for correctly identified patients. We consider that this automated method for patient recognition based on edge-enhanced images would be useful in preventing "wrong" images from being stored in a PACS environment.
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U2 - 10.6009/jjrt.KJ00000921636
DO - 10.6009/jjrt.KJ00000921636
M3 - Article
C2 - 14646995
AN - SCOPUS:1542680311
SN - 0369-4305
VL - 59
SP - 1277
EP - 1284
JO - Nippon Hoshasen Gijutsu Gakkai zasshi
JF - Nippon Hoshasen Gijutsu Gakkai zasshi
IS - 10
ER -