title: [Detection method for blurred regions in radiographs].
abstract: In this paper, we propose a detection method for blurred regions in radiographs. The method involves edge detection using a Sobel filter, manually determining the region of interest (ROI), feature calculation, and classification using a support vector machine. We applied our method to 14 phantom images (7 normal images, 7 blurred images) and 14 clinical images (12 normal images, 2 blurred images). As a result, the average classification accuracies of ROIs with blurring and ROIs without blurring were 98% and 90% for phantom images and clinical images, respectively.
authors.affiliation: Graduate School of Health Sciences, Niigata University.
authors.forename: Tomoya
authors.initials: T
authors.lastname: Muroi
authors.forename: Yongbum
authors.initials: Y
authors.lastname: Lee
authors.forename: Du-Yih
authors.initials: DY
authors.lastname: Tsai
authors.forename: Masaki
authors.initials: M
authors.lastname: Tsurumaki
mesh_terms: D005374:Filtration / Q000379:methods; D019047:Phantoms, Imaging; D011237:Predictive Value of Tests; D011856:Radiographic Image Enhancement / Q000295:instrumentation / Q000379:methods*