A novel approach for the automated segmentation and volume quantification of cardiac fats on computed tomography

• Published in: Computer methods and programs in biomedicine Vol. 123; pp. 109 - 128
• Main Authors: Rodrigues, É.O, Morais, F.F.C, Morais, N.A.O.S, Conci, L.S, Neto, L.V, Conci, A
• Format: Journal Article
• Language: English
• Published: Ireland Elsevier Ireland Ltd 01-01-2016
• Subjects: Adipose Tissue - diagnostic imaging; Algorithms; Classification; Computed tomography; Coronary Artery Disease - diagnostic imaging; Heart - diagnostic imaging; Humans; Image registration; Imaging, Three-Dimensional - methods; Imaging, Three-Dimensional - statistics & numerical data; Internal Medicine; Machine learning; Mediastinum - diagnostic imaging; Medical Informatics; Other; Pericardium - diagnostic imaging; Radiographic Image Interpretation, Computer-Assisted - methods; Segmentation; Tomography, X-Ray Computed - methods; Tomography, X-Ray Computed - statistics & numerical data; Image registration; Atlas; Segmentation; Computed tomography; Classification; Machine learning
• ISSN: 0169-2607; 1872-7565
• DOI: 10.1016/j.cmpb.2015.09.017

Highlights • Proposing an accurate intersubject registration for cardiac CT images. • Proposing and analyzing a hybrid similarity measure that was applied within the registration procedure. • Corroborating on the appliance of classification algorithms for image segmentation. • Analyzing the performance and accuracy of various classifiers for the problem. • Proposing a unified and fully automatic segmentation method for both epicardial and mediastinal fats on cardiac CT images.