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Differentiation of Urinary Stone and Vascular Calcifications on Non-contrast CT Images: An Initial Experience using Computer Aided Diagnosis

Cited 5 time in Web of Science Cited 6 time in Scopus
Authors
Lee, Hak Jong; Kim, Kwang Gi; Hwang, Sung Il; Kim, Seung Hyup; Lee, Sang Eun; Cho, Jeong Yeon; Seong, Chang Gyu; Hong, Seong Kyu; Byun, Seok-Soo
Issue Date
2010-06
Publisher
SPRINGER
Citation
JOURNAL OF DIGITAL IMAGING; Vol.23 3; 268-276
Keywords
Ureter stoneCTcomputer-aided diagnosis
Abstract
The purpose of this study was to develop methods for the differentiation of urinary stones and vascular calcifications using computer-aided diagnosis (CAD) of non-contrast computed tomography (CT) images. From May 2003 to February 2004, 56 patients that underwent a pre-contrast CT examination and subsequently diagnosed as ureter stones were included in the study. Fifty-nine ureter stones and 53 vascular calcifications on pre-contrast CT images of the patients were evaluated. The shapes of the lesions including disperseness, convex hull depth, and lobulation count were analyzed for patients with ureter stones and vascular calcifications. In addition, the internal textures including edge density, skewness, difference histogram variation (DHV), and the gray-level co-occurrence matrix moment were also evaluated for the patients. For evaluation of the diagnostic accuracy of the shape and texture features, an artificial neural network (ANN) and receiver operating characteristics curve (ROC) analyses were performed. Of the several shape factors, disperseness showed a statistical difference between ureter stones and vascular calcifications (p < 0.05). For the internal texture features, skewness and DHV showed statistical differences between ureter stones and vascular calcifications (p < 0.05). The performance of the ANN was evaluated by examining the area under the ROC curves (AUC, A (z)). The A (z) value was 0.85 for the shape parameters and 0.88 for the texture parameters. In this study, several parameters regarding shape and internal texture were statistically different between ureter stones and vascular calcifications. The use of CAD would make it possible to differentiate ureter stones from vascular calcifications by a comparison of these parameters.
ISSN
0897-1889
Language
English
URI
https://hdl.handle.net/10371/78385
DOI
https://doi.org/10.1007/s10278-009-9181-0
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College of Medicine/School of Medicine (의과대학/대학원)Radiology (영상의학전공)Journal Papers (저널논문_영상의학전공)
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