Thomas Lehmann, Abhijit Sovakar, Walter Schmiti and Rudolf Repges,
A comparison of similarity measures for digital
subtraction radiography,
Computers in Biology and Medicine,
27, 2, pp. 151-167, 1997.
Thomas Lehmann, Abhijit Sovakar, Walter Schmiti and Rudolf Repges,
A comparison of similarity measures for digital
subtraction radiography,
Computers in Biology and Medicine,
27, 2, pp. 151-167, 1997.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.