Computer software is frequently used for medical decision support systems in different areas. Magnetic Resonance Images (MRI) are widely used images for brain classification issue. This paper presents an improved method for brain classification of MRI images. The proposed method contains three phases, which are, feature extraction, dimensionality reduction, and an improved classification technique. In the first phase, the features of MRI images are obtained by discrete wavelet transform (DWT). In the second phase, the features of MRI images have been reduced, using principal component analysis (PCA). In the last (third) stage, an improved classifier is developed. In the proposed classifier, Dragonfly algorithm is used instead of backpropagation as training algorithm for artificial neural network (ANN). Some other recent training-based Neural Networks, SVM, and KNN classifiers are used for comparison with the proposed classifier. The classifiers are utilized to classify image as normal or abnormal MRI human brain image. The results show that the proposed classifier is outperformed the other competing classifiers.
DNA has recently been investigated as a possible medium concerning ultra-compact information storage and ultra-scale computation. The development of secure image encryption systems has recently received a certain effective and new direction from chaos-based cryptographic algorithms. This paper proposes a novel image encryption algorithm, 2DNALM, based on double-dynamic DNA sequence encryption and a chaotic 2D logistic map. The three phases regarding the suggested approach are as follows: the first phase involves permuting the positions of the pixels using a position key-based scrambling operation. The second phase involves double DNA encoding on scrambled images using various rules by DNA cryptography concept to produce an encoded image, and in the final step, an image which has been encoded is encrypted using XOR operation and chaotic keys created through a chaotic 2D logistic map. The entropy analysis and experimental findings show that the suggested scheme exhibits great encryption and withstands several common attacks.
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