디지털 유방영상에서 멀티영상 기반의 컴퓨터 보조 진단에 관한 연구
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 최형식 | - |
dc.contributor.author | 조용호 | - |
dc.contributor.author | 조백환 | - |
dc.contributor.author | 문우경 | - |
dc.contributor.author | 임정기 | - |
dc.contributor.author | 김인영 | - |
dc.contributor.author | 김선일 | - |
dc.date.accessioned | 2022-12-21T09:07:36Z | - |
dc.date.available | 2022-12-21T09:07:36Z | - |
dc.date.created | 2022-09-19 | - |
dc.date.issued | 2007-02 | - |
dc.identifier.issn | 1229-0807 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/180451 | - |
dc.description.abstract | For the past decade, the full-field digital mammography has been widely used for early diagnosis of breast cancer, and computer aided diagnosis has been developed to assist physicians as a second opinion. In this study, we try to predict the breast cancer using both mediolateral oblique(MLO) view and craniocaudal(CC) view together. A skilled radiologist selected 35 pairs of ROIs from both MLO view and CC view of digital mammogram. We extracted textural features using Spatial Grey Level Dependence matrix from each mammogram and evaluated the generalization performance of the classifier using Support Vector Machine. We compared the multi-view based classifier to single-view based classifier that is built from each mammogram view. The results represent that the multi-view based computer aided diagnosis in digital mammogram could improve the diagnostic performance and have good possibility for clinical use to assist physicians as a second opinion. | - |
dc.language | 한국어 | - |
dc.language.iso | ko | - |
dc.publisher | 대한의용생체공학회 | - |
dc.title | 디지털 유방영상에서 멀티영상 기반의 컴퓨터 보조 진단에 관한 연구 | - |
dc.title.alternative | A Study on the Multi-View Based Computer Aided Diagnosis in Digital Mammography | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | 김인영 | - |
dc.identifier.bibliographicCitation | 의공학회지, v.28, no.1, pp.162 - 168 | - |
dc.relation.isPartOf | 의공학회지 | - |
dc.citation.title | 의공학회지 | - |
dc.citation.volume | 28 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 162 | - |
dc.citation.endPage | 168 | - |
dc.type.rims | ART | - |
dc.identifier.kciid | ART001056536 | - |
dc.description.journalClass | 2 | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | kci | - |
dc.subject.keywordAuthor | digital mammogram | - |
dc.subject.keywordAuthor | textural features | - |
dc.subject.keywordAuthor | support vector machine | - |
dc.subject.keywordAuthor | multi-view analysis | - |
dc.identifier.url | https://www.kci.go.kr/kciportal/landing/article.kci?arti_id=ART001056536 | - |
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