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Emerging Trends in Artificial Intelligence-Based Urological Imaging Technologies and Practical Applications

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dc.contributor.authorKim, Hyun Suh-
dc.contributor.authorKim, Eun Joung-
dc.contributor.authorKim, Jung Yoon-
dc.date.accessioned2023-12-21T05:30:20Z-
dc.date.available2023-12-21T05:30:20Z-
dc.date.issued2023-11-
dc.identifier.issn2093-4777-
dc.identifier.issn2093-6931-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/89719-
dc.description.abstractThe integration of artificial intelligence (AI) into medical imaging has notably expanded its significance within urology. AI applications offer a broad spectrum of utilities in this domain, ranging from precise diagnosis achieved through image segmentation and anomaly detection to improved procedural assistance in biopsies and surgical interventions. Although challenges persist concerning data security, transparency, and integration into existing clinical workflows, extensive research has been conducted on AI-assisted imaging technologies while recognizing their potential to reshape urological practices. This review paper outlines current AI techniques employed for image analysis to offer an overview of the latest technological trends and applications in the field of urology.-
dc.language영어-
dc.language.isoENG-
dc.publisherKOREAN CONTINENCE SOC-
dc.titleEmerging Trends in Artificial Intelligence-Based Urological Imaging Technologies and Practical Applications-
dc.typeArticle-
dc.identifier.wosid001111259500004-
dc.identifier.doi10.5213/inj.2346286.143-
dc.identifier.bibliographicCitationINTERNATIONAL NEUROUROLOGY JOURNAL, v.27, pp S73 - S81-
dc.identifier.kciidART003020637-
dc.description.isOpenAccessY-
dc.identifier.scopusid2-s2.0-85179608038-
dc.citation.endPageS81-
dc.citation.startPageS73-
dc.citation.titleINTERNATIONAL NEUROUROLOGY JOURNAL-
dc.citation.volume27-
dc.type.docTypeReview-
dc.publisher.location대한민국-
dc.subject.keywordAuthorUrology-
dc.subject.keywordAuthorMedical imaging-
dc.subject.keywordAuthorArtificial intelligence-
dc.subject.keywordAuthorMachine learning-
dc.subject.keywordAuthorApplications-
dc.subject.keywordPlusBLADDER-CANCER-
dc.subject.keywordPlusTEXTURE ANALYSIS-
dc.subject.keywordPlusSEGMENTATION-
dc.relation.journalResearchAreaUrology & Nephrology-
dc.relation.journalWebOfScienceCategoryUrology & Nephrology-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.description.journalRegisteredClasskci-
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