Automatic Transfer Function Design for Medical Direct Volume Rendering via Clustering-Based Ray Analysis
DC Field | Value | Language |
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dc.contributor.author | Jung, Younhyun | - |
dc.date.available | 2021-02-16T00:40:20Z | - |
dc.date.created | 2021-02-16 | - |
dc.date.issued | 2021-04 | - |
dc.identifier.issn | 2156-7018 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/79923 | - |
dc.description.abstract | Transfer Function (TF) design is a central topic in medical direct volume rendering (DVR). TF design allows for interactive identification of features of interest (FOIs) within a medical image volume and their visual emphasis by assigning appropriate optical parameters (opacity and color) to them. Conventional TF design, however, is not intuitive and usually a 'trial-and-error' process for most users. In this work, an automatic TF design scheme is proposed which consists of two-steps. First, I introduce a new clustering-based ray analysis (CRA) to automatically identify FOls along a viewing ray defined by users. Here, the proposed CRA approach uses regional and contextual information around rays to improve the identification capability. Second, the proposed CRA approach automatically generates a TF to emphasize identified FOls by adopting a visibility-driven TF parameter optimization algorithm. Experiments show the effectiveness of the proposed CRA approach by demonstrating its advantages over the existing ray analysis approach relying on local intensity profiles of a ray. I evaluate a number of medical image volume datasets to show the utility of the proposed CRA approach for automatic TF design. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | AMER SCIENTIFIC PUBLISHERS | - |
dc.relation.isPartOf | JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS | - |
dc.title | Automatic Transfer Function Design for Medical Direct Volume Rendering via Clustering-Based Ray Analysis | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000609001300002 | - |
dc.identifier.doi | 10.1166/jmihi.2021.3625 | - |
dc.identifier.bibliographicCitation | JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, v.11, no.4, pp.1055 - 1062 | - |
dc.description.isOpenAccess | N | - |
dc.citation.endPage | 1062 | - |
dc.citation.startPage | 1055 | - |
dc.citation.title | JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS | - |
dc.citation.volume | 11 | - |
dc.citation.number | 4 | - |
dc.contributor.affiliatedAuthor | Jung, Younhyun | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | Direct Volume Rendering | - |
dc.subject.keywordAuthor | Transfer Function | - |
dc.subject.keywordAuthor | Medical Volume Visualization | - |
dc.subject.keywordAuthor | Clustering Analysis | - |
dc.subject.keywordAuthor | Parameter Optimization | - |
dc.subject.keywordPlus | SIMPLEX-METHOD | - |
dc.subject.keywordPlus | VISUALIZATION | - |
dc.subject.keywordPlus | OPTIMIZATION | - |
dc.subject.keywordPlus | EXPLORATION | - |
dc.relation.journalResearchArea | Mathematical & Computational Biology | - |
dc.relation.journalResearchArea | Radiology, Nuclear Medicine & Medical Imaging | - |
dc.relation.journalWebOfScienceCategory | Mathematical & Computational Biology | - |
dc.relation.journalWebOfScienceCategory | Radiology, Nuclear Medicine & Medical Imaging | - |
dc.description.journalRegisteredClass | scie | - |
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