التفاصيل البيبلوغرافية
| العنوان: |
On the Automated Segmentation of Epicardial and Mediastinal Cardiac Adipose Tissues Using Classification Algorithms. |
| المؤلفون: |
Rodrigues ÉO; Institute of Computing, Universidade Federal Fluminense (UFF), Niterói, RJ, Brazil., Cordeiro de Morais FF; School of Medicine, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, RJ, Brazil., Conci A; Institute of Computing, Universidade Federal Fluminense (UFF), Niterói, RJ, Brazil. |
| المصدر: |
Studies in health technology and informatics [Stud Health Technol Inform] 2015; Vol. 216, pp. 726-30. |
| نوع المنشور: |
Evaluation Study; Journal Article; Research Support, Non-U.S. Gov't |
| اللغة: |
English |
| بيانات الدورية: |
Publisher: IOS Press Country of Publication: Netherlands NLM ID: 9214582 Publication Model: Print Cited Medium: Internet ISSN: 1879-8365 (Electronic) Linking ISSN: 09269630 NLM ISO Abbreviation: Stud Health Technol Inform |
| أسماء مطبوعة: |
Original Publication: Amsterdam ; Washington, DC : IOS Press, 1991- |
| مواضيع طبية MeSH: |
Algorithms* , Machine Learning*, Adipose Tissue/*diagnostic imaging , Mediastinum/*diagnostic imaging , Pericardium/*diagnostic imaging , Tomography, X-Ray Computed/*methods, Humans ; Pattern Recognition, Automated/methods ; Radiographic Image Interpretation, Computer-Assisted/methods ; Reproducibility of Results ; Sensitivity and Specificity ; Subtraction Technique |
| مستخلص: |
The quantification of fat depots on the surroundings of the heart is an accurate procedure for evaluating health risk factors correlated with several diseases. However, this type of evaluation is not widely employed in clinical practice due to the required human workload. This work proposes a novel technique for the automatic segmentation of cardiac fat pads. The technique is based on applying classification algorithms to the segmentation of cardiac CT images. Furthermore, we extensively evaluate the performance of several algorithms on this task and discuss which provided better predictive models. Experimental results have shown that the mean accuracy for the classification of epicardial and mediastinal fats has been 98.4% with a mean true positive rate of 96.2%. On average, the Dice similarity index, regarding the segmented patients and the ground truth, was equal to 96.8%. Therfore, our technique has achieved the most accurate results for the automatic segmentation of cardiac fats, to date. |
| تواريخ الأحداث: |
Date Created: 20150812 Date Completed: 20161213 Latest Revision: 20191210 |
| رمز التحديث: |
20221213 |
| PMID: |
26262147 |
| قاعدة البيانات: |
MEDLINE |
