1997
@article{LSS1997,
vgclass = {refpap},
author = {Thomas Lehmann and Abhijit Sovakar and Walter Schmiti
and Rudolf Repges},
title = {A comparison of similarity measures for digital
subtraction radiography},
journal = {Computers in Biology and Medicine},
volume = {27},
number = {2},
pages = {151--167},
year = {1997},
abstract = {Subtraction is useful in detecting small changes in
sequentially acquired radiographs. Even if the imaging geometry is
constant, radiographs must be registered after their digltization. To
compare different algorithms for image registration and to register
digital X-rays themselves, various similarity measures have been
proposed. This study compares eight mathematical similarity standards
using 172 radiographs acquired in different, but exactly known
projection. Whenever the computation time is a critical factor, e.g.
registering images using methods similar to correlation techniques, the
entropy of the subtraction image's histogram function (EHDI) is found
to be the best similarity standard. If not, e.g. comparative assessing
different image registration techniques, the cross covariance
coefficient (CCC) is appropriate.},
}