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Adaptive Image Rescaling for Weakly Contrast-Enhanced Lesions in Dedicated Breast CT: A Phantom Study

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dc.contributor.author김진성-
dc.date.accessioned2022-09-14T01:43:02Z-
dc.date.available2022-09-14T01:43:02Z-
dc.date.issued2021-11-
dc.identifier.issn1738-2637-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/190584-
dc.description.abstractPurpose Dedicated breast CT is an emerging volumetric X-ray imaging modality for diagnosis that does not require any painful breast compression. To improve the detection rate of weakly enhanced lesions, an adaptive image rescaling (AIR) technique was proposed. Materials and Methods Two disks containing five identical holes and five holes of different diameters were scanned using 60/100 kVp to obtain single-energy CT (SECT), dual-energy CT (DECT), and AIR images. A piece of pork was also scanned as a subclinical trial. The image quality was evaluated using image contrast and contrast-to-noise ratio (CNR). The difference of imaging performances was confirmed using student's t test. Results Total mean image contrast of AIR (0.70) reached 74.5% of that of DECT (0.94) and was higher than that of SECT (0.22) by 318.2%. Total mean CNR of AIR (5.08) was 35.5% of that of SECT (14.30) and was higher than that of DECT (2.28) by 222.8%. A similar trend was observed in the subclinical study. Conclusion The results demonstrated superior image contrast of AIR over SECT, and its higher overall image quality compared to DECT with half the exposure. Therefore, AIR seems to have the potential to improve the detectability of lesions with dedicated breast CT.-
dc.description.statementOfResponsibilityopen-
dc.languageKorean-
dc.publisher대한영상의학회-
dc.relation.isPartOfJournal of the Korean Society of Radiology(대한영상의학회지)-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleAdaptive Image Rescaling for Weakly Contrast-Enhanced Lesions in Dedicated Breast CT: A Phantom Study-
dc.title.alternative약하게 조영증강된 병변의 유방 전용 CT 영상의 대조도 개선을 위한 적응적 영상 재조정 방법: 팬텀 연구-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Radiation Oncology (방사선종양학교실)-
dc.contributor.googleauthorBitbyeol Kim-
dc.contributor.googleauthorHo Kyung Kim-
dc.contributor.googleauthorJinsung Kim-
dc.contributor.googleauthorYongkan Ki-
dc.contributor.googleauthorJi Hyeon Joo-
dc.contributor.googleauthorHosang Jeon-
dc.contributor.googleauthorDahl Park-
dc.contributor.googleauthorWontaek Kim-
dc.contributor.googleauthorJiho Nam-
dc.contributor.googleauthorDong Hyeon Kim-
dc.identifier.doi10.3348/jksr.2020.0191-
dc.contributor.localIdA04548-
dc.relation.journalcodeJ01843-
dc.identifier.eissn2288-2928-
dc.subject.keywordBreast Cancer-
dc.subject.keywordComputed Tomography , X-Ray-
dc.subject.keywordContrast Agent-
dc.subject.keywordImage Quality Enhancement-
dc.contributor.alternativeNameKim, Jinsung-
dc.contributor.affiliatedAuthor김진성-
dc.citation.volume82-
dc.citation.number6-
dc.citation.startPage1477-
dc.citation.endPage1492-
dc.identifier.bibliographicCitationJournal of the Korean Society of Radiology (대한영상의학회지), Vol.82(6) : 1477-1492, 2021-11-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiation Oncology (방사선종양학교실) > 1. Journal Papers

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