Computerized analysis of digital subtraction angiography: a tool for quantitative in-vivo vascular imaging.
The purpose of our study was to develop a user-independent computerized tool for the automated segmentation and quantitative assessment of in vivo-acquired digital subtraction angiography (DSA) images. Vessel enhancement was accomplished based on the concept of image structural tensor. The developed...
| Publicado en: | Journal of Digital Imaging Vol. 21; no. 4; pp. 433 - 446 |
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| Autores principales: | , , , , , , , , , , |
| Formato: | diagnostic images equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Dec2008
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105569269&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105569269 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Dec2008 vid: 21 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 105569269 2010092422 10.1007/s10278-007-9047-2 NLM17674102 105569269 ppf: 433 ppct: 13 formats: fmt: @attributes: type: P tig: atl: Computerized analysis of digital subtraction angiography: a tool for quantitative in-vivo vascular imaging. aug: au: Kagadis G Spyridonos P Karnabatidis D Diamantopoulos A Athanasiadis E Daskalakis A Katsanos K Cavouras D Mihailidis D Siablis D Nikiforidis G affil: Department of Medical Physics, School of Medicine, University of Patras, 265 00 Rion, Greece sug: subj: Angiography, Digital Subtraction Blood Vessels Radiography Radiographic Image Interpretation, Computer-Assisted Radiographic Magnification Algorithms Evaluation Research False Negative Results False Positive Results Funding Source Neovascularization, Physiologic ROC Curve Software Human ab: The purpose of our study was to develop a user-independent computerized tool for the automated segmentation and quantitative assessment of in vivo-acquired digital subtraction angiography (DSA) images. Vessel enhancement was accomplished based on the concept of image structural tensor. The developed software was tested on a series of DSA images acquired from one animal and two human angiogenesis models. Its performance was evaluated against manually segmented images. A receiver's operating characteristic curve was obtained for every image with regard to the different percentages of the image histogram. The area under the mean curve was 0.89 for the experimental angiogenesis model and 0.76 and 0.86 for the two clinical angiogenesis models. The coordinates of the operating point were 8.3% false positive rate and 92.8% true positive rate for the experimental model. Correspondingly for clinical angiogenesis models, the coordinates were 8.6% false positive rate and 89.2% true positive rate and 9.8% false positive rate and 93.8% true positive rate, respectively. A new user-friendly tool for the analysis of vascular networks in DSA images was developed that can be easily used in either experimental or clinical studies. Its main characteristics are robustness and fast and automatic execution. pubtype: Academic Journal doctype: diagnostic images equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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