TY - JOUR
T1 - Development of a method of automated extraction of biological fingerprints from chest radiographs as preprocessing of patient recognition and identification
AU - Shimizu, Yoichiro
AU - Morishita, Junji
N1 - Publisher Copyright:
© 2017, Japanese Society of Radiological Technology and Japan Society of Medical Physics.
PY - 2017/9/1
Y1 - 2017/9/1
N2 - This paper describes the development of an automated method of extraction of biological fingerprints (BFs), including detection of image orientation in chest radiographs. The image orientation of a target image was recognized and modified by examination of normalized cross-correlation values between a target image and averaged male and female images with correct image orientation. Templates of BFs were extracted from averaged images. Then, each BF in the target image was extracted from locations that showed the highest cross-correlation value between the template of BF in the averaged image and the corresponding BF in the target image. With our method, 100% (200/200) of image orientations were recognized correctly. If the orientation was recognized as inappropriate, our algorithm modified it into the appropriate chest image orientation. In addition, the BFs automatically extracted from target images were improved. This method would be useful in a preprocessing system for patient recognition and identification.
AB - This paper describes the development of an automated method of extraction of biological fingerprints (BFs), including detection of image orientation in chest radiographs. The image orientation of a target image was recognized and modified by examination of normalized cross-correlation values between a target image and averaged male and female images with correct image orientation. Templates of BFs were extracted from averaged images. Then, each BF in the target image was extracted from locations that showed the highest cross-correlation value between the template of BF in the averaged image and the corresponding BF in the target image. With our method, 100% (200/200) of image orientations were recognized correctly. If the orientation was recognized as inappropriate, our algorithm modified it into the appropriate chest image orientation. In addition, the BFs automatically extracted from target images were improved. This method would be useful in a preprocessing system for patient recognition and identification.
UR - http://www.scopus.com/inward/record.url?scp=85018257553&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85018257553&partnerID=8YFLogxK
U2 - 10.1007/s12194-017-0400-y
DO - 10.1007/s12194-017-0400-y
M3 - Article
C2 - 28452001
AN - SCOPUS:85018257553
SN - 1865-0333
VL - 10
SP - 376
EP - 381
JO - Radiological physics and technology
JF - Radiological physics and technology
IS - 3
ER -