Density Invariant Detection of Osteoporosis Using Growing Neural Gas
Tytuł:
Density Invariant Detection of Osteoporosis Using Growing Neural Gas
Czasopismo:
PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON COMPUTER RECOGNITION SYSTEMS CORES 2013
Rok:
2013
Opis:
We present a method for osteoporosis detection using graph representations
obtained running a Growing Neural Gas machine learning algorithm on X–ray bone images.
The GNG induced graph, being dependent on density, represents well the features which
may be in part responsible for the illness. The graph connects well dense bone regions,
making it possible to subdivide the whole image into regions. It is interesting to note, that
these regions in bones, whose extraction might make it easie
Strony:
629-638
Tom (seria wydawnicza):
Springer International Publishing
Link:
http://link.springer.com/chapter/10.1007/978-3-319-00969-8_62