Literature DB >> 27132238

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

Yoichiro Shimizu1, Yusuke Matsunobu2, Junji Morishita3.   

Abstract

We have been developing an image-searching method to identify misfiled images in a PACS server. Developing new biological fingerprints (BFs) that would reduce the influence of differences in positioning and breathing phases to improve the performance of recognition is desirable. In our previous studies, the whole lung field (WLF) that included the shadows of the body and lungs was affected by differences in positioning and/or breathing phases. In this study, we showed the usefulness of a circumscribed lung with a rectangular region of interest and the upper half of a chest radiograph as modified BFs. We used 200 images as hypothetically misfiled images. The cross-correlation identifies the resemblance between the BFs in the misfiled images and the corresponding BFs in the database images. The modified BFs indicated better results than did WLF in a receiver operating characteristic analysis; therefore, they could be used as identifiers for patient recognition and identification.

Entities:  

Keywords:  Biological fingerprints; Digital chest radiograph; Patient identification; Picture archiving and communication system

Mesh:

Year:  2016        PMID: 27132238     DOI: 10.1007/s12194-016-0355-4

Source DB:  PubMed          Journal:  Radiol Phys Technol        ISSN: 1865-0333


  8 in total

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

Authors:  J Morishita; S Katsuragawa; K Kondo; K Doi
Journal:  Med Phys       Date:  2001-06       Impact factor: 4.071

2.  Automated patient identity recognition by analysis of chest radiograph features.

Authors:  E-Fong Kao; Wei-Chen Lin; Twei-Shiun Jaw; Gin-Chung Liu; Jain-Shing Wu; Chung-Nan Lee
Journal:  Acad Radiol       Date:  2013-08       Impact factor: 3.173

3.  Image feature analysis for computer-aided diagnosis: accurate determination of ribcage boundary in chest radiographs.

Authors:  X W Xu; K Doi
Journal:  Med Phys       Date:  1995-05       Impact factor: 4.071

4.  Clinical usefulness of temporal subtraction method in screening digital chest radiography with a mobile computed radiography system.

Authors:  Yasuo Sasaki; Katsumi Abe; Makiko Tabei; Shigehiko Katsuragawa; Atsuko Kurosaki; Shoji Matsuoka
Journal:  Radiol Phys Technol       Date:  2010-12-18

5.  Investigation of misfiled cases in the PACS environment and a solution to prevent filing errors for chest radiographs.

Authors:  Junji Morishita; Hideyuki Watanabe; Shigehiko Katsuragawa; Nobuhiro Oda; Yoshiharu Sukenobu; Hiroko Okazaki; Hajime Nakata; Kunio Doi
Journal:  Acad Radiol       Date:  2005-01       Impact factor: 3.173

6.  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

7.  Potential usefulness of biological fingerprints in chest radiographs for automated patient recognition and identification.

Authors:  Junji Morishita; Shigehiko Katsuragawa; Yasuo Sasaki; Kunio Doi
Journal:  Acad Radiol       Date:  2004-03       Impact factor: 3.173

8.  [Development of an automated patient-recognition method for digital chest radiographs using edge-enhanced images].

Authors:  Keisuke Kondo; Junji Morishita; Shigehiko Katsuragawa; Kunio Doi
Journal:  Nihon Hoshasen Gijutsu Gakkai Zasshi       Date:  2003-10
  8 in total
  3 in total

1.  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

2.  Development of a computer-aided quality assurance support system for identifying hand X-ray image direction using deep convolutional neural network.

Authors:  Mitsuru Sato; Yohan Kondo; Masashi Okamoto
Journal:  Radiol Phys Technol       Date:  2022-08-24

3.  Biological fingerprint for patient verification using trunk scout views at various scan ranges in computed tomography.

Authors:  Yasuyuki Ueda; Junji Morishita; Shohei Kudomi
Journal:  Radiol Phys Technol       Date:  2022-09-26
  3 in total

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