Literature DB >> 11439478

An automated patient recognition method based on an image-matching technique using previous chest radiographs in the picture archiving and communication system environment.

J Morishita1, S Katsuragawa, K Kondo, K Doi.   

Abstract

An automated patient recognition method for correcting "wrong" chest radiographs being stored in a picture archiving and communication system (PACS) environment has been developed. The method is based on an image-matching technique that uses previous chest radiographs. For identification of a "wrong" patient, the correlation value was determined for a previous image of a patient and a new, current image of the presumed corresponding patient. The current image was shifted horizontally and vertically and rotated, so that we could determine the best match between the two images. The results indicated that the correlation values between the current and previous images for the same, "correct" patients were generally greater than those for different, "wrong" patients. Although the two histograms for the same patient and for different patients overlapped at correlation values greater than 0.80, most parts of the histograms were separated. The correlation value was compared with a threshold value that was determined based on an analysis of the histograms of correlation values obtained for the same patient and for different patients. If the current image is considered potentially to belong to a "wrong" patient, then a warning sign with the probability for a "wrong" patient is provided to alert radiology personnel. Our results indicate that at least half of the "wrong" images in our database can be identified correctly with the method described in this study. The overall performance in terms of a receiver operating characteristic curve showed a high performance of the system. The results also indicate that some readings of "wrong" images for a given patient in the PACS environment can be prevented by use of the method we developed. Therefore an automated warning system for patient recognition would be useful in correcting "wrong" images being stored in the PACS environment.

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Year:  2001        PMID: 11439478     DOI: 10.1118/1.1373403

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  14 in total

1.  Evaluation of the image quality of temporal subtraction images produced automatically in a PACS environment.

Authors:  Shuji Sakai; Hiroyasu Soeda; Akio Furuya; Hidetake Yabuuchi; Takashi Okafuji; Keiji Yamamoto; Hiroshi Honda; Kunio Doi
Journal:  J Digit Imaging       Date:  2006-12       Impact factor: 4.056

2.  Development of a method of automated extraction of biological fingerprints from chest radiographs as preprocessing of patient recognition and identification.

Authors:  Yoichiro Shimizu; Junji Morishita
Journal:  Radiol Phys Technol       Date:  2017-04-27

3.  Radiation dose reduction with frame rate conversion in X-ray fluoroscopic imaging systems with flat panel detector: basic study and clinical retrospective analysis.

Authors:  Noriyuki Sakai; Katsuyuki Tabei; Jiro Sato; Toshikazu Imae; Yuichi Suzuki; Shigeharu Takenaka; Keiichi Yano; Osamu Abe
Journal:  Eur Radiol       Date:  2018-07-09       Impact factor: 5.315

4.  Improving image quality around subtle lung nodules by reducing artifacts in similar subtraction imaging.

Authors:  Hitomi Nakamura; Junji Morishita; Yoichiro Shimizu; Yongsu Yoon; Yusuke Matsunobu; Shigehiko Katsuragawa; Hidetake Yabuuchi
Journal:  Radiol Phys Technol       Date:  2018-09-05

5.  Evaluation of the usefulness of modified biological fingerprints in chest radiographs for patient recognition and identification.

Authors:  Yoichiro Shimizu; Yusuke Matsunobu; Junji Morishita
Journal:  Radiol Phys Technol       Date:  2016-04-30

6.  Evaluation of the depiction ability of similar subtraction images using digital chest radiographs of different patients.

Authors:  Yoichiro Shimizu; Junji Morishita; Yusuke Matsunobu; Yongsu Yoon; Yasuo Sasaki; Shigehiko Katsuragawa; Hidetake Yabuuchi
Journal:  Radiol Phys Technol       Date:  2018-11-20

7.  Computer-aided nodule detection on digital chest radiography: validation test on consecutive T1 cases of resectable lung cancer.

Authors:  Shuji Sakai; Hiroyasu Soeda; Naoki Takahashi; Takashi Okafuji; Tadamasa Yoshitake; Hidetake Yabuuchi; Ichiro Yoshino; Keiji Yamamoto; Hiroshi Honda; Kunio Doi
Journal:  J Digit Imaging       Date:  2006-12       Impact factor: 4.056

8.  Computerized image-searching method for finding correct patients for misfiled chest radiographs in a PACS server by use of biological fingerprints.

Authors:  Risa Toge; Junji Morishita; Yasuo Sasaki; Kunio Doi
Journal:  Radiol Phys Technol       Date:  2013-06-15

9.  A multiobserver study of the effects of including point-of-care patient photographs with portable radiography: a means to detect wrong-patient errors.

Authors:  Srini Tridandapani; Senthil Ramamurthy; James Provenzale; Nancy A Obuchowski; Michael G Evanoff; Pamela Bhatti
Journal:  Acad Radiol       Date:  2014-08       Impact factor: 3.173

10.  Usefulness of biological fingerprint in magnetic resonance imaging for patient verification.

Authors:  Yasuyuki Ueda; Junji Morishita; Shohei Kudomi; Katsuhiko Ueda
Journal:  Med Biol Eng Comput       Date:  2015-09-04       Impact factor: 2.602

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