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

نویسندگان

  • Jorge G Barbosa
  • Bruno Figueiredo
  • Nuno Bettencourt
  • João Manuel R S Tavares
چکیده

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.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Semi-automatic quantification of the epicardial fat in CT images

In this work we present a technique to automatically or semi-automatically quantify the epicardial fat in noncontrasted Computed Tomography (CT) images. In CT images, the epicardial fat is very close to the pericardial fat, distincted only by the pericardium. The pericardium appears in the image as a very thin line, very hard to discriminate. To enhance the pericardium line and to remove noise ...

متن کامل

Automatic quantification of epicardial fat volume on non-enhanced cardiac CT scans using a multi-atlas segmentation approach.

PURPOSE There is increasing evidence that epicardial fat (i.e., adipose tissue contained within the pericardium) plays an important role in the development of cardiovascular disease. Obtaining the epicardial fat volume from routinely performed non-enhanced cardiac CT scans is therefore of clinical interest. The purpose of this work is to investigate the feasibility of automatic pericardium segm...

متن کامل

Semiautomatic Epicardial Fat Segmentation Based on Fuzzy c-Means Clustering and Geometric Ellipse Fitting

Automatic segmentation of particular heart parts plays an important role in recognition tasks, which is utilized for diagnosis and treatment. One particularly important application is segmentation of epicardial fat (surrounds the heart), which is shown by various studies to indicate risk level for developing various cardiovascular diseases as well as to predict progression of certain diseases. ...

متن کامل

Automatic classification of Non-alcoholic fatty liver using texture features from ultrasound images

Background: Accurate and early detection of non-alcoholic fatty liver, which is a major cause of chronic diseases is very important and is vital to prevent the complications associated with this disease. Ultrasound of the liver is the most common and widely performed method of diagnosing fatty liver. However, due to the low quality of ultrasound images, the need for an automatic and intelligent...

متن کامل

Non-invasive quantification of liver fat content by different Gradient Echo MRI sequences in patients with Non-Alcoholic Fatty Liver Disease (NAFLD)

Introduction: Non-invasive quantification of liver fat by Gradient echo (GRE) Technique is an interesting issue in quantitative MRI. Despite the numerous advantages of this technique, fat measurement maybe biased by confounding and effects. The aim of this study was to evaluate the GRE pulse sequences with different   and  weighting for liver fat quantification in patients with...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Computer methods in biomechanics and biomedical engineering

دوره 14 10  شماره 

صفحات  -

تاریخ انتشار 2011