Evaluation of the usefulness of modified biological fingerprints in chest radiographs for patient recognition and identification
| Autor: | Yoichiro Shimizu, Yusuke Matsunobu, Junji Morishita |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Male
medicine.medical_specialty Databases Factual Radiography Physical Therapy Sports Therapy and Rehabilitation Patient Positioning 030218 nuclear medicine & medical imaging Patient identification 03 medical and health sciences 0302 clinical medicine Picture archiving and communication system Region of interest Image Processing Computer-Assisted Humans Medicine Radiology Nuclear Medicine and imaging Lung Radiation medicine.diagnostic_test Receiver operating characteristic analysis business.industry Respiration Pattern recognition General Medicine Surgery Identification (information) 030220 oncology & carcinogenesis Female Radiography Thoracic Artificial intelligence business Chest radiograph Lung field |
| Zdroj: | Radiological Physics and Technology. 9:240-244 |
| ISSN: | 1865-0341 1865-0333 |
| DOI: | 10.1007/s12194-016-0355-4 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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