1. Home page
  2. Search

Application of Kohonen network for automatic point correspondence in 2D medical images

This item is provided by the institution :
National Technical University of Athens   

Repository :
Digital Library of National Technical University of Athens | Dspace@NTUA   

see the original item page
in the repository's web site and access all digital files if the item*



Application of Kohonen network for automatic point correspondence in 2D medical images (EN)
Asvestas, PA (EN)
Markaki, VE (EN)
Matsopoulos, GK (EN)
journalArticle (EN)
2014-03-01T01:29:52Z
2009 (EN)
In this paper, a generalized application of Kohonen Network for automatic point correspondence of unimodal medical images is presented. Given a pair of two-dimensional medical images of the same anatomical region and a set of interest points in one of the images, the algorithm detects effectively the set of corresponding points in the second image, by exploiting the properties of the Kohonen self organizing maps (SOMs) and embedding them in a stochastic optimization framework. The correspondences are established by determining the parameters of local transformations that map the interest points of the first image to their corresponding points in the second image. The parameters of each transformation are computed in an iterative way, using a modification of the competitive learning, as implemented by SOMs. The proposed algorithm was tested on medical imaging data from three different modalities (CT, MR and red-free retinal images) subject to known and unknown transformations. The quantitative results in all cases exhibited sub-pixel accuracy. The algorithm also proved to work efficiently in the case of noise corrupted data. Finally. in comparison to a previously published algorithm that was also based on SOMs, as well as two widely used techniques for detection of point correspondences (template matching and iterative closest point), the proposed algorithm exhibits an improved performance in terms of accuracy and robustness. (C) 2009 Elsevier Ltd. All rights reserved. (EN)
Computer Science, Interdisciplinary Applications (EN)
Engineering, Biomedical (EN)
Biology (EN)
Mathematical & Computational Biology (EN)
artificial neural network (EN)
Brain (EN)
Parameter estimation (EN)
Automatic correspondence (EN)
nuclear magnetic resonance imaging (EN)
Humans (EN)
Medical images (EN)
Point extraction (EN)
Retina (EN)
Tomography, X-Ray Computed (EN)
learning (EN)
Iterative closest point (EN)
image analysis (EN)
clinical article (EN)
retina image (EN)
Education (EN)
nuclear magnetic resonance scanner (EN)
Kohonen network (EN)
priority journal (EN)
quantitative analysis (EN)
computer assisted tomography (EN)
human (EN)
algorithm (EN)
Neural Networks (Computer) (EN)
Global transformation (EN)
Medical imaging (EN)
Similarity measure (EN)
Template matching (EN)
article (EN)
Local transformation (EN)
Magnetic Resonance Imaging (EN)
Algorithms (EN)
Self organizing maps (EN)
Image Processing, Computer-Assisted (EN)
Set theory (EN)
computed tomography scanner (EN)
Computers in Biology and Medicine (EN)
English
PERGAMON-ELSEVIER SCIENCE LTD (EN)
National Technical University of Athens
Digital Library of National Technical University of Athens | Dspace@NTUA
Κεντρική Βιβλιοθήκη Ε.Μ.Π.
Ιδρυματικό Αποθετήριο
Δημοσιεύσεις μελών Δ.Ε.Π. σε περιοδικά



*Institutions are responsible for keeping their URLs functional (digital file, item page in repository site)