Cited 8 times in
Mammographic Density Assessment by Artificial Intelligence-Based Computer-Assisted Diagnosis: A Comparison with Automated Volumetric Assessment
DC Field | Value | Language |
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dc.contributor.author | 김은경 | - |
dc.contributor.author | 이시은 | - |
dc.date.accessioned | 2022-05-09T17:01:26Z | - |
dc.date.available | 2022-05-09T17:01:26Z | - |
dc.date.issued | 2022-04 | - |
dc.identifier.issn | 0897-1889 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/188338 | - |
dc.description.abstract | We evaluated and compared the mammographic density assessment of an artificial intelligence-based computer-assisted diagnosis (AI-CAD) program using inter-rater agreements between radiologists and an automated density assessment program. Between March and May 2020, 488 consecutive mammograms of 488 patients (56.2 ± 10.9 years) were collected from a single institution. We assigned four classes of mammographic density based on BI-RADS (Breast Imaging Reporting and Data System) using commercial AI-CAD (Lunit INSIGHT MMG), and compared inter-rater agreements between radiologists, AI-CAD, and another commercial automated density assessment program (Volpara®). The inter-rater agreement between AI-CAD and the reader consensus was 0.52 with a matched rate of 68.2% (333/488). The inter-rater agreement between Volpara® and the reader consensus was similar to AI-CAD at 0.50 with a matched rate of 62.7% (306/488). The inter-rater agreement between AI-CAD and Volpara® was 0.54 with a matched rate of 61.5% (300/488). In conclusion, density assessments by AI-CAD showed fair agreement with those of radiologists, similar to the agreement between the commercial automated density assessment program and radiologists. | - |
dc.description.statementOfResponsibility | restriction | - |
dc.language | English | - |
dc.publisher | Springer | - |
dc.relation.isPartOf | JOURNAL OF DIGITAL IMAGING | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.subject.MESH | Artificial Intelligence | - |
dc.subject.MESH | Breast Density* | - |
dc.subject.MESH | Breast Neoplasms* / diagnostic imaging | - |
dc.subject.MESH | Computers | - |
dc.subject.MESH | Female | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Mammography / methods | - |
dc.subject.MESH | Retrospective Studies | - |
dc.title | Mammographic Density Assessment by Artificial Intelligence-Based Computer-Assisted Diagnosis: A Comparison with Automated Volumetric Assessment | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Radiology (영상의학교실) | - |
dc.contributor.googleauthor | Si Eun Lee | - |
dc.contributor.googleauthor | Nak-Hoon Son | - |
dc.contributor.googleauthor | Myung Hyun Kim | - |
dc.contributor.googleauthor | Eun-Kyung Kim | - |
dc.identifier.doi | 10.1007/s10278-021-00555-x | - |
dc.contributor.localId | A00801 | - |
dc.contributor.localId | A05611 | - |
dc.relation.journalcode | J01379 | - |
dc.identifier.eissn | 1618-727X | - |
dc.identifier.pmid | 35015180 | - |
dc.identifier.url | https://link.springer.com/article/10.1007/s10278-021-00555-x | - |
dc.subject.keyword | Artificial intelligence | - |
dc.subject.keyword | Breast density | - |
dc.subject.keyword | Diagnosis, Computer-assisted | - |
dc.subject.keyword | Digital mammography | - |
dc.contributor.alternativeName | Kim, Eun Kyung | - |
dc.contributor.affiliatedAuthor | 김은경 | - |
dc.contributor.affiliatedAuthor | 이시은 | - |
dc.citation.volume | 35 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 173 | - |
dc.citation.endPage | 179 | - |
dc.identifier.bibliographicCitation | JOURNAL OF DIGITAL IMAGING, Vol.35(2) : 173-179, 2022-04 | - |
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