A Large Scale Analysis for Testing a Mathematical Model for the Study of Vascular Pathologies
In this paper, we carry out a study developed on 13,677 images from 15 patients affected by moderate/severe atheromatous disease of the abdominal aortic tract. A procedure to extract the pervious lumen of the aorta artery from basal CT images is exploited and tested on a large scale. In particular,...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/11/8/1831 |
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| author | Arianna Travaglini Gianluca Vinti Giovanni Battista Scalera Michele Scialpi |
| author_facet | Arianna Travaglini Gianluca Vinti Giovanni Battista Scalera Michele Scialpi |
| author_sort | Arianna Travaglini |
| collection | DOAJ |
| description | In this paper, we carry out a study developed on 13,677 images from 15 patients affected by moderate/severe atheromatous disease of the abdominal aortic tract. A procedure to extract the pervious lumen of the aorta artery from basal CT images is exploited and tested on a large scale. In particular, the above method takes advantage of the reconstruction and enhancing properties of the sampling Kantorovich algorithm which allows the information content of images to be increased. The processed image is compared, slice by slice, by superposition, with the corresponding contrast medium reference image. Numerical indices of errors were computed and analyzed in order to test the validity of the proposed method. The results achieved confirm, both from the numerical and clinical point of view, the good performance and accuracy of the proposed method, opening the possibility to perform an assisted diagnosis avoiding the injection of the contrast medium. |
| first_indexed | 2024-03-11T04:47:08Z |
| format | Article |
| id | doaj.art-e168320a8b2749d595fb07d5b4535079 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-11T04:47:08Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-e168320a8b2749d595fb07d5b45350792023-11-17T20:17:09ZengMDPI AGMathematics2227-73902023-04-01118183110.3390/math11081831A Large Scale Analysis for Testing a Mathematical Model for the Study of Vascular PathologiesArianna Travaglini0Gianluca Vinti1Giovanni Battista Scalera2Michele Scialpi3Department of Mathematics and Computer Science, University of Perugia, 1, Via Vanvitelli, 06123 Perugia, ItalyDepartment of Mathematics and Computer Science, University of Perugia, 1, Via Vanvitelli, 06123 Perugia, ItalyDivision of Diagnostic Imaging, Department of Medicine and Surgery, University of Perugia, Santa Maria della Misericordia Hospital, 3, Piazzale Giorgio Menghini, 06129 Perugia, ItalyDivision of Diagnostic Imaging, Department of Medicine and Surgery, University of Perugia, Santa Maria della Misericordia Hospital, 3, Piazzale Giorgio Menghini, 06129 Perugia, ItalyIn this paper, we carry out a study developed on 13,677 images from 15 patients affected by moderate/severe atheromatous disease of the abdominal aortic tract. A procedure to extract the pervious lumen of the aorta artery from basal CT images is exploited and tested on a large scale. In particular, the above method takes advantage of the reconstruction and enhancing properties of the sampling Kantorovich algorithm which allows the information content of images to be increased. The processed image is compared, slice by slice, by superposition, with the corresponding contrast medium reference image. Numerical indices of errors were computed and analyzed in order to test the validity of the proposed method. The results achieved confirm, both from the numerical and clinical point of view, the good performance and accuracy of the proposed method, opening the possibility to perform an assisted diagnosis avoiding the injection of the contrast medium.https://www.mdpi.com/2227-7390/11/8/1831sampling Kantorovich operatorsapproximation resultsdigital image processingsimilarity indicescomputed tomographyabdominal aortic aneurysm |
| spellingShingle | Arianna Travaglini Gianluca Vinti Giovanni Battista Scalera Michele Scialpi A Large Scale Analysis for Testing a Mathematical Model for the Study of Vascular Pathologies Mathematics sampling Kantorovich operators approximation results digital image processing similarity indices computed tomography abdominal aortic aneurysm |
| title | A Large Scale Analysis for Testing a Mathematical Model for the Study of Vascular Pathologies |
| title_full | A Large Scale Analysis for Testing a Mathematical Model for the Study of Vascular Pathologies |
| title_fullStr | A Large Scale Analysis for Testing a Mathematical Model for the Study of Vascular Pathologies |
| title_full_unstemmed | A Large Scale Analysis for Testing a Mathematical Model for the Study of Vascular Pathologies |
| title_short | A Large Scale Analysis for Testing a Mathematical Model for the Study of Vascular Pathologies |
| title_sort | large scale analysis for testing a mathematical model for the study of vascular pathologies |
| topic | sampling Kantorovich operators approximation results digital image processing similarity indices computed tomography abdominal aortic aneurysm |
| url | https://www.mdpi.com/2227-7390/11/8/1831 |
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