Evaluation of Texture for Classification of Abdominal Aortic Aneurysm After Endovascular Repair.
The use of the endovascular prostheses in abdominal aortic aneurysm has proven to be an effective technique to reduce the pressure and rupture risk of aneurysm. Nevertheless, in a long-term perspective, complications such as leaks inside the aneurysm sac (endoleaks) could appear causing a pressure e...
| Publicado en: | Journal of Digital Imaging Vol. 25; no. 3; pp. 369 - 377 |
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| Autores principales: | , , , |
| Formato: | diagnostic images equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jun2012
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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=104564884&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104564884 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Jun2012 vid: 25 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104564884 75063752 10.1007/s10278-011-9417-7 NLM21901536 104564884 ppf: 369 ppct: 8 formats: fmt: @attributes: type: P tig: atl: Evaluation of Texture for Classification of Abdominal Aortic Aneurysm After Endovascular Repair. aug: au: García, Guillermo Maiora, Josu Tapia, Arantxa Blas, Mariano affil: University of the Basque Country, Systems Engineering and Automatic Department, Polytechnical University College, Plaza Europa 1 20018 San Sebastian Spain sug: subj: Aortic Aneurysm, Abdominal Surgery Blood Vessel Prosthesis Postoperative Complications Diagnosis Image Processing, Computer Assisted Methods Neural Networks (Computer) Angiography Tomography, X-Ray Computed Outcome Assessment Methods Algorithms Evaluation Research ROC Curve Descriptive Statistics Middle Age Aged Human Middle Aged: 45-64 years Aged: 65+ years ab: The use of the endovascular prostheses in abdominal aortic aneurysm has proven to be an effective technique to reduce the pressure and rupture risk of aneurysm. Nevertheless, in a long-term perspective, complications such as leaks inside the aneurysm sac (endoleaks) could appear causing a pressure elevation and increasing the danger of rupture consequently. At present, computed tomographic angiography (CTA) is the most common examination for medical surveillance. However, endoleak complications cannot always be detected by visual inspection on CTA scans. The investigation on new techniques to detect endoleaks and analyse their effects on treatment evolution is of great importance for endovascular aneurysm repair (EVAR) technique. The purpose of this work was to evaluate the capability of texture features obtained from the aneurysmatic thrombus CT images to discriminate different types of evolutions caused by endoleaks. The regions of interest (ROIs) from patients with different post-EVAR evolution were extracted by experienced radiologists. Three techniques were applied to each ROI to obtain texture parameters, namely the grey level co-occurrence matrix (GLCM), the grey level run length matrix (GLRLM) and the grey level difference method (GLDM). The results showed that GLCM, GLRLM and GLDM features presented a good discrimination ability to differentiate between favourable or unfavourable evolutions. GLCM was the most efficient in terms of classification accuracy (93.41% ± 0.024) followed by GLRLM (90.17% ± 0.077) and finally by GLDM (81.98% ± 0.045). According to the results, we can consider texture analysis as complementary information to classified abdominal aneurysm evolution after EVAR. 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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