<博士論文>
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

作成者
論文調査委員
本文言語
学位授与年度
学位授与大学
学位
学位種別
出版タイプ
アクセス権
関連DOI
概要 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 o...f 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.
続きを見る

本文ファイル

pdf dent0775 pdf 1.98 MB 224 本文
pdf dent0775_abstract pdf 65.9 KB 93 要旨
pdf dent0775_review pdf 145 KB 104 審査結果要旨

詳細

レコードID
査読有無
権利関係
関連PubMed ID
報告番号
学位記番号
授与日(学位/助成/特許)
受理日
部局
登録日 2018.11.05
更新日 2018.11.26

この資料を見た人はこんな資料も見ています