دورية أكاديمية
A novel approach for the automated segmentation and volume quantification of cardiac fats on computed tomography.
| العنوان: | A novel approach for the automated segmentation and volume quantification of cardiac fats on computed tomography. |
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| المؤلفون: | Rodrigues ÉO; Department of Computer Science, Universidade Federal Fluminense (UFF), Rua Passo da Pátria 156, Niterói, Rio de Janeiro, Brazil. Electronic address: erickr@id.uff.br., Morais FF; Department of Internal Medicine and Endocrine Unit, Medical School and Hospital Universitário Clementino Fraga Filho, Universidade Federal do Rio de Janeiro (UFRJ), Rua Rodolpho Paulo Rocco, 255 - Cidade Universitária, Rio de Janeiro, Brazil., Morais NA; Department of Internal Medicine and Endocrine Unit, Medical School and Hospital Universitário Clementino Fraga Filho, Universidade Federal do Rio de Janeiro (UFRJ), Rua Rodolpho Paulo Rocco, 255 - Cidade Universitária, Rio de Janeiro, Brazil., Conci LS; Department of Specialized Medicine, Universidade Federal do Espírito Santo (UFES), Av. Marechal Campos, 1468 - Maruípe, Vitória, Brazil., Neto LV; Department of Internal Medicine and Endocrine Unit, Medical School and Hospital Universitário Clementino Fraga Filho, Universidade Federal do Rio de Janeiro (UFRJ), Rua Rodolpho Paulo Rocco, 255 - Cidade Universitária, Rio de Janeiro, Brazil., Conci A; Department of Computer Science, Universidade Federal Fluminense (UFF), Rua Passo da Pátria 156, Niterói, Rio de Janeiro, Brazil. |
| المصدر: | Computer methods and programs in biomedicine [Comput Methods Programs Biomed] 2016 Jan; Vol. 123, pp. 109-28. Date of Electronic Publication: 2015 Sep 30. |
| نوع المنشور: | Journal Article; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: Elsevier Scientific Publishers Country of Publication: Ireland NLM ID: 8506513 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1872-7565 (Electronic) Linking ISSN: 01692607 NLM ISO Abbreviation: Comput Methods Programs Biomed Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: Limerick : Elsevier Scientific Publishers Original Publication: Amsterdam : Elsevier Science Publishers, c1984- |
| مواضيع طبية MeSH: | Algorithms*, Adipose Tissue/*diagnostic imaging , Heart/*diagnostic imaging , Radiographic Image Interpretation, Computer-Assisted/*methods , Tomography, X-Ray Computed/*methods, Coronary Artery Disease/diagnostic imaging ; Humans ; Imaging, Three-Dimensional/methods ; Imaging, Three-Dimensional/statistics & numerical data ; Mediastinum/diagnostic imaging ; Medical Informatics ; Pericardium/diagnostic imaging ; Tomography, X-Ray Computed/statistics & numerical data |
| مستخلص: | The deposits of fat on the surroundings of the heart are correlated to several health risk factors such as atherosclerosis, carotid stiffness, coronary artery calcification, atrial fibrillation and many others. These deposits vary unrelated to obesity, which reinforces its direct segmentation for further quantification. However, manual segmentation of these fats has not been widely deployed in clinical practice due to the required human workload and consequential high cost of physicians and technicians. In this work, we propose a unified method for an autonomous segmentation and quantification of two types of cardiac fats. The segmented fats are termed epicardial and mediastinal, and stand apart from each other by the pericardium. Much effort was devoted to achieve minimal user intervention. The proposed methodology mainly comprises registration and classification algorithms to perform the desired segmentation. We compare the performance of several classification algorithms on this task, including neural networks, probabilistic models and decision tree algorithms. Experimental results of the proposed methodology have shown that the mean accuracy regarding both epicardial and mediastinal fats is 98.5% (99.5% if the features are normalized), with a mean true positive rate of 98.0%. In average, the Dice similarity index was equal to 97.6%. (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.) |
| فهرسة مساهمة: | Keywords: Atlas; Classification; Computed tomography; Image registration; Machine learning; Segmentation |
| تواريخ الأحداث: | Date Created: 20151018 Date Completed: 20160919 Latest Revision: 20161126 |
| رمز التحديث: | 20231215 |
| DOI: | 10.1016/j.cmpb.2015.09.017 |
| PMID: | 26474835 |
| قاعدة البيانات: | MEDLINE |
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Full Text Finder | تدمد: | 1872-7565 |
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| DOI: | 10.1016/j.cmpb.2015.09.017 |