Kannan, Balakrishnan; Abraham, Varghese; Reji, Rajan Varghese; Joseph, Paul S(The British Computer Society, October 22, 2013)
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Abstract:
Retrieval of similar anatomical structures of brain MR images across patients would help the expert
in diagnosis of diseases. In this paper, modified local binary pattern with ternary encoding called
modified local ternary pattern (MOD-LTP) is introduced, which is more discriminant and less
sensitive to noise in near-uniform regions, to locate slices belonging to the same level from the brain
MR image database. The ternary encoding depends on a threshold, which is a user-specified one
or calculated locally, based on the variance of the pixel intensities in each window. The variancebased
local threshold makes the MOD-LTP more robust to noise and global illumination changes.
The retrieval performance is shown to improve by taking region-based moment features of MODLTP
and iteratively reweighting the moment features of MOD-LTP based on the user’s feedback.
The average rank obtained using iterated and weighted moment features of MOD-LTP with a local
variance-based threshold, is one to two times better than rotational invariant LBP (Unay, D., Ekin,
A. and Jasinschi, R.S. (2010) Local structure-based region-of-interest retrieval in brain MR images.
IEEE Trans. Inf. Technol. Biomed., 14, 897–903.) in retrieving the first 10 relevant images