Differentiation of urinary stone and vascular calcifications on non-contrast CT images: an initial experience using computer aided diagnosis.
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 su...
| Published in: | Journal of Digital Imaging Vol. 23; no. 3; pp. 268 - 277 |
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| Main Authors: | , , , , , , , , |
| Format: | diagnostic images equations & formulas research tables/charts Journal Article |
| Published: |
Springer Nature
Jun2010
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105202688&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105202688 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Jun2010 vid: 23 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 105202688 2010656976 10.1007/s10278-009-9181-0 NLM19190962 105202688 ppf: 268 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Differentiation of urinary stone and vascular calcifications on non-contrast CT images: an initial experience using computer aided diagnosis. aug: au: Lee HJ Kim KG Hwang SI Kim SH Byun S Lee S Hong SK Cho JY Seong CG affil: Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea sug: subj: Calcinosis Diagnosis Diagnosis, Computer Assisted Urolithiasis Diagnosis Adult Diagnosis, Differential Female Funding Source Human Male Middle Age Retrospective Design ROC Curve T-Tests Tomography, X-Ray Computed Adult: 19-44 years Middle Aged: 45-64 years Female Male ab: 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, Az). The Az 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. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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