Abstract
Traditionally, cardiac image analysis is done manually. Automatic image processing can help with the repetitive tasks, and also deal with huge amounts of data, a task which would be humanly tedious. This study aims to develop a spectrum-based computer-aided tool to locate the left ventricle using images obtained via cardiac magnetic resonance imaging. Discrete Fourier Transform was conducted pixelwise on the image sequence. Harmonic images of all frequencies were analyzed visually and quantitatively to determine different patterns of the left and right ventricles on spectrum. The first and fifth harmonic images were selected to perform an anisotropic weighted circle Hough detection. This tool was then tested in ten volunteers. Our tool was able to locate the left ventricle in all cases and had a significantly higher cropping ratio of 0.165 than did earlier studies. In conclusion, a new spectrum-based computer aided tool has been proposed and developed for automatic left ventricle localization. The development of this technique, which will enable the automatic location and further segmentation of the left ventricle, will have a significant impact in research and in diagnostic settings. We envisage that this automated method could be used by radiographers and cardiologists to diagnose and assess ventricular function in patients with diverse heart diseases.
Highlights
Cardiovascular Disease (CVD) is currently the leading cause of death, killing 17.3 million people worldwide each year
A new spectrum-based computer-aided tool has been proposed and developed for automatic left ventricle (LV) localization.We found that the right ventricle (RV) presented higher brightness than the LV in all harmonic images
The combination of the first and fifth harmonic images selected for an anisotropic weighted circle Hough detector was found to be the most robust for locating the LV
Summary
Cardiovascular Disease (CVD) is currently the leading cause of death, killing 17.3 million people worldwide each year. This figure represents one-third of total death, a proportion that is still increasing. The examination and analysis of medical cardiac images is of great significance for diagnosis and treatment. The reliability of quantitative assessment of cardiac functions such as muscle deformation and ventricular ejection fraction is dependent on the precision and correctness of the heart chamber segmentation [2]. This segmentation task is performed manually via software assistance, which is quite time-consuming.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
