Full metadata record
| DC pole | Hodnota | Jazyk |
|---|---|---|
| dc.contributor.author | Gabriel, František | |
| dc.contributor.author | Kursová, Lucie | |
| dc.date.accessioned | 2019-11-11T11:00:22Z | - |
| dc.date.available | 2019-11-11T11:00:22Z | - |
| dc.date.issued | 2019 | |
| dc.identifier.citation | VČELÁK, P., KRYL, M., KRATOCHVÍL, M., KLEČKOVÁ, J. Identification and classification of DICOM files with burned-in text content. International Journal of Medical Informatics, 2019, roč. 126, č. JUN 2019, s. 128-137. ISSN 1386-5056. | en |
| dc.identifier.issn | 0231-5823 | |
| dc.identifier.uri | 2-s2.0-85063996088 | |
| dc.identifier.uri | http://hdl.handle.net/11025/35858 | |
| dc.description.abstract | Označení ganerbenburg považují někteří autoři za dispoziční typ hradů. Článek upozorňuje na chybnost tohoto přístupu a doporučuje užívání jiného druhového jména a jeho definici. | cs |
| dc.format | 10 s. | cs |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en | en |
| dc.publisher | Elsevier | en |
| dc.relation.ispartofseries | International Journal of Medical Informatics | en |
| dc.rights | Plný text je přístupný v rámci univerzity přihlášeným uživatelům. | cs |
| dc.rights | © Elsevier | en |
| dc.title | Typové zařazení hradu Skála u Přeštic | cs |
| dc.title.alternative | Typological classification of the Skála castle, near Přeštice | en |
| dc.type | článek | cs |
| dc.type | article | en |
| dc.rights.access | restrictedAccess | en |
| dc.type.version | publishedVersion | en |
| dc.description.abstract-translated | Background: Protected health information burned in pixel data is not indicated for various reasons in DICOM. It complicates the secondary use of such data. In recent years, there have been several attempts to anonymize or de-identify DICOM files. Existing approaches have different constraints. No completely reliable solution exists. Especially for large datasets, it is necessary to quickly analyse and identify files potentially violating privacy. Methods: Classification is based on adaptive-iterative algorithm designed to identify one of three classes. There are several image transformations, optical character recognition, and filters; then a local decision is made. A confirmed local decision is the final one. The classifier was trained on a dataset composed of 15,334 images of various modalities. Results: The false positive rates are in all cases below 4.00%, and 1.81% in the mission-critical problem of detecting protected health information. The classifier's weighted average recall was 94.85%, the weighted average inverse recall was 97.42% and Cohen's Kappa coefficient was 0.920. Conclusion: The proposed novel approach for classification of burned-in text is highly configurable and able to analyse images from different modalities with a noisy background. The solution was validated and is intended to identify DICOM files that need to have restricted access or be thoroughly de-identified due to privacy issues. Unlike with existing tools, the recognised text, including its coordinates, can be further used for de-identification. | en |
| dc.subject.translated | castle | en |
| dc.subject.translated | Middle Ages | en |
| dc.subject.translated | castle core | en |
| dc.identifier.doi | 10.5817/AH2019-2-3 | |
| dc.type.status | Peer-reviewed | en |
| dc.identifier.obd | 43926908 | |
| dc.project.ID | LO1506/PUNTIS - Podpora udržitelnosti centra NTIS - Nové technologie pro informační společnost | cs |
| Vyskytuje se v kolekcích: | Články / Articles (NTIS) Články / Articles (KIV) OBD | |
Soubory připojené k záznamu:
| Soubor | Velikost | Formát | |
|---|---|---|---|
| Gabriel - Kursová[1].pdf | 868,07 kB | Adobe PDF | Zobrazit/otevřít |
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