Logarithmic Fuzzy Entropy Function for Similarity Measurement in Multimodal Medical Images Registration

Abstract

Multimodal medical images are useful for observing tissue structure clearly in clinical practice. To integrate multimodal information, multimodal registration is significant. The entropy-based registration applies a structure descriptor set to replace the original multimodal image and compute similarity to express the correlation of images. The accuracy and converging rate of the registration depend on this set. We propose a new method, logarithmic fuzzy entropy function, to compute the descriptor set. It is obvious that the proposed method can increase the upper bound value from log(r) to log(r) + ∆(r) so that a more representative structural descriptor set is formed. The experiment results show that our method has faster converging rate and wider quantified range in multimodal medical images registration.

A New Feature Analysis Approach to Selecting Channels of EEG for Fatigue Driving

“…The concept of fuzzy entropy (FE) was first proposed by Chen et al [ 15 ] in 2007. FE describes the fuzziness of a fuzzy set [ 16 ] and measures the probability of a new pattern being generated. The larger the measure, the greater the probability of the new pattern being generated and the greater the sequence complexity.…”

“…In the experiments of this paper, firstly, the sampling frequency of EEG signal was reduced to 128 Hz, secondly, a sixlayer wavelet packet decomposition tree was built, and then the original EEG signal was decomposed into four subbands, including Theta subband (4-8 Hz), Alpha subband (8-13 Hz), Beta1 subband (13)(14)(15)(16)(17)(18)(19)(20), and Beta2 subband (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30). Finally, the standard deviation (Std) features are extracted for each subband, and the best performing subband features are fused with the fuzzy entropy features to form the fused features.…”

“…The names of the electrodes correspond to their positions as follows: Fp1 (1), Fp2 (2), F7 (3), F3 (4), Fz (5), F4 (6), F8 (7), FT7 (8), FC3 (9), FCz (10), FC4 (11), FT8 (12), T3 (13), C3 (14), Cz (15), C4 (16), T4 (17), TP7 (18), CP3 (19), CPz (20), CP4 (21), TP8 (22), T5 (23), P3 (24), Pz (25), P4 (26), T6 (27), O1 (28), Oz (29), and O2 (30).…”