Towards automatic quantification of the epicardial fat in non-contrasted CT images

被引：27

作者：

Barbosa, Jorge G. ^{[1
]}

Figueiredo, Bruno ^{[1
]}

Bettencourt, Nuno ^{[2
]}

Tavares, Joao Manuel R. S. ^{[3
]}

机构：

[1] Univ Porto, Fac Engn, Dept Informat Engn, Lab Inteligencia Artificial & Ciencia Comp, P-4200465 Oporto, Portugal

[2] Ctr Hosp Gaia, Dept Cardiol, Vn Gaia, Portugal

[3] Univ Porto, Fac Engn, Dept Engn Mecan, Inst Engn Mecan & Gestao Ind, P-4200465 Oporto, Portugal

来源：

COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING | 2011年 / 14卷 / 10期

关键词：

anatomical model-based segmentation; clustering; low-contrasted images; polynomial interpolation; ADIPOSE-TISSUE; ABDOMINAL FAT; OBESITY; RISK; SEGMENTATION; DISEASE;

D O I：

10.1080/10255842.2010.499871

中图分类号：

TP39 [计算机的应用];

学科分类号：

080201 [机械制造及其自动化];

摘要：

In this work, we present a technique to semi-automatically quantify the epicardial fat in non-contrasted computed tomography (CT) images. The epicardial fat is very close to the pericardial fat, being separated only by the pericardium that appears in the image as a very thin line, which is hard to detect. Therefore, an algorithm that uses the anatomy of the heart was developed to detect the pericardium line via control points of the line. From the points detected an interpolation was applied based on the cubic interpolation, which was also improved to avoid incorrect interpolation that occurs when the two variables are non-monotonic. The method is validated by using a set of 40 CT images of the heart of 40 human subjects. In 62.5% of the cases only minimal user intervention was required and the results compared favourably with the results obtained by the manual process.

引用

页码：905 / 914

页数：10

共 19 条

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