Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/3638
Title: Automatic Landmark Location for Analysis of Cardiac MRI Images
Authors: Christodoulou, Chris
Jayne, Chrisina
Alexakis, Dimitrios 
Lanitis, Andreas 
Keywords: Attention to details
Automatic location
Cardiac images
Landmark locations
Landmarks locations
Neural network method
Radial basis functions
Shape modelling
Neural networks
Radial basis function networks
Magnetic resonance imaging
Issue Date: 2012
Publisher: Springer Berlin Heidelberg
Source: 13th International Conference Proceedings, EANN 2012, United Kingdom, Volume 311, Pages 203-212
Abstract: This paper addresses the problem of automatic location of landmarks used for the analysis of MRI cardiac images. Typically the landmarks of shapes in MRI images are located manually which is a time consuming process requiring human expertise and attention to detail. As an alternative a number of researchers use shape modelling and image search techniques for locating the required landmarks automatically. Usually these techniques require human expertise for initializing the search and in addition they require high quality, noise free images so that the image-based landmark location is successful. With our work we propose the use of neural network methods for learning the geometry of sets of points so that it is possible to predict the positions of all required landmarks based on the positions of a small subset of the landmarks rather than using image-data during the process of landmark-location. As part of our work the performance of neural network methods like Multilayer Perceptrons, Radial Basis Functions and Support Vector Machines is evaluated. Quantitative and visual results demonstrate the potential of using such methods for locating the required landmarks on endo-cardial and epicardial landmarks of the left ventricle of MRI cardiac images. Springer-Verlag Berlin Heidelberg 2012.
URI: http://ktisis.cut.ac.cy/jspui/handle/10488/3638
ISSN: 18650929
DOI: 10.1007/978-3-642-32909-8_21
Rights: Springer-Verlag Berlin Heidelberg
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers

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