Multi-modality medical images fusion based on local-features fuzzy sets and novel sum-modified-Laplacian in non-subsampled shearlet transform domain

2020 ◽  
Vol 57 ◽  
pp. 101724 ◽  
Author(s):  
Hikmat Ullah ◽  
Basharat Ullah ◽  
Longwen Wu ◽  
Fakheraldin Y.O. Abdalla ◽  
Guanghui Ren ◽  
...  
Keyword(s):  
Fuzzy Sets ◽  
Medical Images ◽  
Local Features ◽  
Transform Domain ◽  
Shearlet Transform

Medical Image Fusion Method Based on Coupled Neural P Systems in Nonsubsampled Shearlet Transform Domain

2020 ◽  
Vol 31 (01) ◽  
pp. 2050050 ◽  
Author(s):  
Bo Li ◽  
Hong Peng ◽  
Xiaohui Luo ◽  
Jun Wang ◽  
Xiaoxiao Song ◽  
...  
Keyword(s):  
Image Fusion ◽  
Medical Images ◽  
Low Frequency ◽  
Transform Domain ◽  
Fusion Method ◽  
Shearlet Transform ◽  
Nonsubsampled Shearlet Transform ◽  
Model Combining ◽  
Fusion Methods ◽  
Image Fusion Method

Coupled neural P (CNP) systems are a recently developed Turing-universal, distributed and parallel computing model, combining the spiking and coupled mechanisms of neurons. This paper focuses on how to apply CNP systems to handle the fusion of multi-modality medical images and proposes a novel image fusion method. Based on two CNP systems with local topology, an image fusion framework in nonsubsampled shearlet transform (NSST) domain is designed, where the two CNP systems are used to control the fusion of low-frequency NSST coefficients. The proposed fusion method is evaluated on 20 pairs of multi-modality medical images and compared with seven previous fusion methods and two deep-learning-based fusion methods. Quantitative and qualitative experimental results demonstrate the advantage of the proposed fusion method in terms of visual quality and fusion performance.

Robust and Secured Medical Image Watermarking Using Daub4 and CoAST Transforms

2018 ◽  
Vol 8 (9) ◽  
pp. 1857-1864
Author(s):  
V. Kavitha ◽  
C. Palanisamy ◽  
T. Sureshkumar
Keyword(s):  
Medical Image ◽  
Medical Images ◽  
Image Watermarking ◽  
Singular Values ◽  
Jpeg Compression ◽  
Experimental Results ◽  
Watermark Image ◽  
Shearlet Transform ◽  
Medical Image Watermarking ◽  
Hybrid Watermarking

A hybrid watermarking technique using wavelet and Shearlet transform is proposed in this paper. The DWT variant Daub4 transform model is applied on the medical image to generate different frequency sub-bands. The HL and LH sub-bands which are resistant to compression attacks are chosen for second level of transformation, a DST variant 'Cone adaptive Shearlet transform' technique is used to calculate the Shearlet coefficients of the selected sub-bands. By using SVD on the Shearlet coefficients, the singular values of watermark image are embedded into the singular values of the host image. The proposed approach is examined using three medical images and a watermark image. The experimental results show that the proposed approach is robust against JPEG compression, Geometric and Noise attacks.

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