Automatic localization of the left ventricle from cardiac cine magnetic resonance imaging: a new spectrum-based computer-aided tool.
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.
Bioengineering Department, National Heart Centre Singapore, Singapore, Singapore; Cardiovascular & Metabolic Disorders Program, Duke-NUS Graduate Medical School Singapore, Singapore, Singapore.
Liang
L
Zhong
Bioengineering Department, National Heart Centre Singapore, Singapore, Singapore.
Jun-Mei
JM
Zhang
Bioengineering Department, National Heart Centre Singapore, Singapore, Singapore.
Xiaodan
X
Zhao
Bioengineering Department, National Heart Centre Singapore, Singapore, Singapore; Cardiovascular & Metabolic Disorders Program, Duke-NUS Graduate Medical School Singapore, Singapore, Singapore.
Ru San
RS
Tan
Bioengineering Department, National Heart Centre Singapore, Singapore, Singapore; Geometrical Modelling, Institute of High Performance Computing, A*STAR, Singapore, Singapore.
Min
M
Wan
D000328:Adult; D000465:Algorithms; D016880:Anisotropy; D001331:Automation; D002309:Cardiology / Q000379:methods; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D005583:Fourier Analysis; D064368:Healthy Volunteers; D006352:Heart Ventricles / Q000473:pathology*; D006801:Humans; D019028:Magnetic Resonance Imaging, Cine / Q000379:methods*; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D012984:Software; D016277:Ventricular Function, Left