Cluster signal-to-noise analysis for evaluation of the information content in an image
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- Material Type
- 博士論文
- Author/Editor
- ワラーンカナー, ウィーラワーニッチ
- Publication Date
- 2018-09-25
- Publication Date (W3CDTF)
- 2018-09-25
- Alternative Title
- 画像情報評価のためのクラスターシグナルノイズ分析法
- Contributor
- 築山, 能大三木, 洋一郎牧平, 清超
- Degree Grantor
- 九州大学
- Date Granted
- 2018-09-25
- Date Granted (W3CDTF)
- 2018-09-25
- Dissertation Number
- 甲第14187号
- Degree Type
- 博士（歯学）
- Conferring No. (Dissertation)
- 甲第14187号
- Text Language Code
- eng
- Note (General)
- Objectives：(1) To develop an observer-free method of analysing image quality related to the observer performance in the detection task and (2) to analyse observer behaviour patterns in the detection of small mass changes in cone-beam CT images. / Methods：13 observers detected holes in a Teflon phantom in cone-beam CT images. Using the same images, we developed a new method, cluster signal-to-noise analysis, to detect the holes by applying various cut-off values using ImageJ and reconstructing cluster signal-to-noise curves. We then evaluated the correlation between cluster signal-to-noise analysis and the observer performance test. We measured the background noise in each image to evaluate the relationship with false positive rates (FPRs) of the observers. Correlations between mean FPRs and intra- and interobserver variations were also evaluated. Moreover, we calculated true positive rates (TPRs) and accuracies from background noise and evaluated their correlations with TPRs from observers. / Results：Cluster signal-to-noise curves were derived in cluster signal-to-noise analysis. They yield the detection of signals (true holes) related to noise (false holes). This method correlated highly with the observer performance test (R2 = 0.9296). In noisy images, increasing background noise resulted in higher FPRs and larger intra- and interobserver variations. TPRs and accuracies calculated from background noise had high correlation with actual TPRs from observers; R2 was 0.9244 and 0.9338, respectively. / Conclusions：Cluster signal-to-noise analysis can simulate the detection performance of observers and thus replace the observer performance test in the evaluation of image quality. Erroneous decision-making increased with increasing background noise.PubMed番号 : 28749736元資料の権利情報 : © 2018 The Authors. Published by the British Institute of Radiology
- DOI
- info:doi/10.1259/dmfr.20170147
- Persistent ID (NDL)
- info:ndljp/pid/11194626
- Collection
- Collection (Materials For Handicapped People:1)
- Collection (particular)
- 国立国会図書館デジタルコレクション > デジタル化資料 > 博士論文
- Acquisition Basis
- 博士論文（自動収集）
- Date Accepted (W3CDTF)
- 2018-12-03T16:15:19+09:00
- Date Created (W3CDTF)
- 2018-11-05
- Format (IMT)
- application/pdf
- Access Restrictions
- 国立国会図書館内限定公開
- Service for the Digitized Contents Transmission Service
- 図書館・個人送信対象外
- Availability of remote photoduplication service
- 可
- Periodical Title (URI)
- Data Provider (Database)
- 国立国会図書館 : 国立国会図書館デジタルコレクション