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IEEE Transactions on Instrumentation and Measurement, 2019
As an effective way to integrate the information contained in multiple medical images with different modalities, medical image fusion has emerged as a powerful technique in various clinical applications such as disease diagnosis and treatment planning ...
M. Yin, Xiaoning Liu, Yu Liu, Xun Chen
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As an effective way to integrate the information contained in multiple medical images with different modalities, medical image fusion has emerged as a powerful technique in various clinical applications such as disease diagnosis and treatment planning ...
M. Yin, Xiaoning Liu, Yu Liu, Xun Chen
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2023 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA), 2023
Breast cancer is the most common form of cancer in women and the second leading cause of cancer death in this group. It is difficult, however, to diagnose cancer.
C. Sarada, K. Lakshmi, M. Padmavathamma
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Breast cancer is the most common form of cancer in women and the second leading cause of cancer death in this group. It is difficult, however, to diagnose cancer.
C. Sarada, K. Lakshmi, M. Padmavathamma
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Continuous Modulated Shearlet Transform
Advances in Pure and Applied Mathematics, 2022Summary: We generalize the well-known transforms such as short-time Fourier transform, wavelet transform and shearlet transform and refer it as Continuous Modulated Shearlet Transform. Important properties like Plancherel formula and inversion formula have been investigated. Uncertainty inequalities associated with this transform are presented.
Bansal, Piyush +2 more
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IEEE Transactions on Image Processing, 2009
In this paper, a new type of deconvolution algorithm is proposed that is based on estimating the image from a shearlet decomposition. Shearlets provide a multidirectional and multiscale decomposition that has been mathematically shown to represent distributed discontinuities such as edges better than traditional wavelets.
Vishal M. Patel +2 more
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In this paper, a new type of deconvolution algorithm is proposed that is based on estimating the image from a shearlet decomposition. Shearlets provide a multidirectional and multiscale decomposition that has been mathematically shown to represent distributed discontinuities such as edges better than traditional wavelets.
Vishal M. Patel +2 more
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Shearlets: Theory and Applications
GAMM-Mitteilungen, 2014AbstractMany important problem classes are governed by anisotropic features such as singularities concentrated on lower dimensional embedded manifolds, for instance, edges in images or shock fronts in solutions of transport dominated equations. While the ability to reliably capture and sparsely represent anisotropic structures is obviously the more ...
Kutyniok, Gitta +2 more
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Edges and Corners With Shearlets
IEEE Transactions on Image Processing, 2015Shearlets are a relatively new and very effective multi-scale framework for signal analysis. Contrary to the traditional wavelets, shearlets are capable to efficiently capture the anisotropic information in multivariate problem classes. Therefore, shearlets can be seen as the valid choice for multi-scale analysis and detection of directional sensitive ...
DUVAL POO, MIGUEL ALEJANDRO +2 more
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, 2021
Medical images usually display various attributes of data on human viscera and abnormal tissue in different modalities. The fusion of images, ensures effective deployment of all relevant information from several modalities into a single image.
Rekha R. Nair, Tripty Singh
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Medical images usually display various attributes of data on human viscera and abnormal tissue in different modalities. The fusion of images, ensures effective deployment of all relevant information from several modalities into a single image.
Rekha R. Nair, Tripty Singh
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A new construction of shearlets
Infinite Dimensional Analysis, Quantum Probability and Related Topics, 2022In order to achieve optimally sparse approximations of signals exhibiting anisotropic singularities, the shearlet systems that are systems of functions generated by one generator with dilation, shear transformation and translation operators applied to it were introduced.
Pooran Ghaderihasab, Ahmad Ahmadi
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Deep Shearlet Network for Change Detection in SAR Images
IEEE Transactions on Geoscience and Remote Sensing, 2022Convolutional neural networks (CNNs) can extract shift-invariant features and have been widely applied in the change detection task. However, common CNN lacks noise robustness and needs supervised data to alleviate these problems; in this article, we ...
Huihui Dong +6 more
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Sparse-Promoting 3-D Airborne Electromagnetic Inversion Based on Shearlet Transform
IEEE Transactions on Geoscience and Remote Sensing, 2022The conventional, L2-norm-based, regularization term in electromagnetic (EM) inversions implements smooth constraints on model complexity in the space domain, which can smoothen the boundaries of complex underground structures.
Yang Su +7 more
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