Literature DB >> 36155890

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

Yasuyuki Ueda1, Junji Morishita2, Shohei Kudomi3.   

Abstract

Immediate verification of whether a patient being examined is correct is desirable, even if the scan ranges change during different examinations for the same patient. This study proposes an advanced biological fingerprint technique for the rapid and reliable verification of various scan ranges in computed tomography (CT) scans of the torso of the same patient. The method comprises the following steps: geometric correction of different scans, local feature extraction, mismatch elimination, and similarity evaluation. The geometric magnification correction was aligned at the scanner table height in the first two steps, and the local maxima were calculated as the local features. In the third step, local features from the follow-up scout image are matched to those in the corresponding baseline scout image via template matching and outlier elimination via a robust estimator. We evaluated the correspondence rate based on the inlier ratio between corresponding scout images. The ratio of inliers between the baseline and follow-up scout images was assessed as the similarity score. The clinical dataset, including chest, abdomen-pelvis, and chest-abdomen-pelvis scans, included 600 patients (372 men, 68 ± 12 years) who underwent two routine torso CT examinations. The highest area under the receiver operating characteristic curve (AUC) was 0.996, which was sufficient for patient verification. Moreover, the verification results were comparable to the conventional method, which uses scout images in the same scan range. Patient identity verification was achieved before the main scan, even in follow-up torso CT, under different scan ranges.
© 2022. The Author(s), under exclusive licence to Japanese Society of Radiological Technology and Japan Society of Medical Physics.

Entities:  

Keywords:  Biological fingerprint; Biometrics; Computed tomography; Patient verification; Scout image

Year:  2022        PMID: 36155890     DOI: 10.1007/s12194-022-00682-2

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


  27 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.  Is it possible to eliminate patient identification errors in medical imaging?

Authors:  Luke A Danaher; Joan Howells; Penny Holmes; Peter Scally
Journal:  J Am Coll Radiol       Date:  2011-08       Impact factor: 5.532

Review 3.  New solutions for automated image recognition and identification: challenges to radiologic technology and forensic pathology.

Authors:  Junji Morishita; Yasuyuki Ueda
Journal:  Radiol Phys Technol       Date:  2021-03-12

4.  Biological fingerprint using scout computed tomographic images for positive patient identification.

Authors:  Yasuyuki Ueda; Junji Morishita; Tadashi Hongyo
Journal:  Med Phys       Date:  2019-09-06       Impact factor: 4.071

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.  Registration-associated patient misidentification in an academic medical center: causes and corrections.

Authors:  Mark J Bittle; Patricia Charache; Daniel M Wassilchalk
Journal:  Jt Comm J Qual Patient Saf       Date:  2007-01

Review 7.  Patient misidentification in oncology care.

Authors:  Lisa Schulmeister
Journal:  Clin J Oncol Nurs       Date:  2008-06       Impact factor: 1.027

8.  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

9.  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

10.  Patient identification errors are common in a simulated setting.

Authors:  Philip L Henneman; Donald L Fisher; Elizabeth A Henneman; Tuan A Pham; Megan M Campbell; Brian H Nathanson
Journal:  Ann Emerg Med       Date:  2009-12-23       Impact factor: 5.721

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.