DocumentCode
117972
Title
Parametric models for segmentation of Cardiac MRI database with geometrical interpretation
Author
Bhan, Anupama
Author_Institution
Dept. of Electron. & Commun. Eng., Amity Univ., Noida, India
fYear
2014
fDate
20-21 Feb. 2014
Firstpage
711
Lastpage
715
Abstract
There are several medical image modalities which enable a proper diagnosis of Heart Diseases. Magnetic Resonance imaging is one of the most non invasive techniques used by radiologist for diagnosis nowadays. Segmentation of Cardiac MRI is basically dividing the heart into left and right ventricle, where left ventricle plays a vital role. In this paper the segmentation of Left Ventricle using parametric model is done which helps to calculate geometrical parameters. These parameters further helps to distinguish between an abnormal and normal heart. The segmentation is carried out on multi slice MRI frame. Parametric model used in this paper is Active Contour Model which is also called as Snake Model or Deformable model. The geometrical analysis is shown graphically to show the difference between different patient databases. The clinical diagnosis is also made on the physiological parameters like volume of blood and ejection fraction which will be the future extension to this paper.
Keywords
biomedical MRI; cardiology; geometry; image segmentation; medical image processing; patient diagnosis; radiology; active contour model; cardiac MRI database; clinical diagnosis; deformable model; geometrical interpretation; heart diseases; image segmentation; magnetic resonance imaging; medical image modalities; parametric models; patient databases; patient diagnosis; radiology; snake model; Active contours; Equations; Heart; Image edge detection; Image segmentation; Magnetic resonance imaging; Vectors; Active contour models; deformable models; gradient vector flow; image segmentation; snakes;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing and Integrated Networks (SPIN), 2014 International Conference on
Conference_Location
Noida
Print_ISBN
978-1-4799-2865-1
Type
conf
DOI
10.1109/SPIN.2014.6777047
Filename
6777047
Link To Document