Results 101 to 110 of about 6,475 (267)
In vivo T2 measurements of the fetal brain using single‐shot fast spin echo sequences
Abstract Purpose We propose a quantitative framework for motion‐corrected T2 fetal brain measurements in vivo and validate the single‐shot fast spin echo (SS‐FSE) sequence to perform these measurements. Methods Stacks of two‐dimensional SS‐FSE slices are acquired with different echo times (TE) and motion‐corrected with slice‐to‐volume reconstruction ...
Suryava Bhattacharya+11 more
wiley +1 more source
Linear independence of compactly supported separable shearlet systems
This paper examines linear independence of shearlet systems. This property has already been studied for wavelets and other systems such as, for instance, for Gabor systems.
Ma, Jackie, Petersen, Philipp
core +1 more source
This paper introduces a novel infrared and visible image fusion network to address the limitations of auto‐encoder fusion networks. In the designed network, the encoder employs a multi‐branch cascade structure with convolution kernels of different sizes to extract multi‐scale features, and the fusion layer incorporates a non‐local attention module ...
Jing Xu, Zhenjin Liu, Ming Fang
wiley +1 more source
An Enhanced Approach of Image Steganographic Using Discrete Shearlet Transform and Secret Sharing
في الآونة الأخيرة، جعل الإنترنت المستخدمين قادرين على نقل الوسائط الرقمية بطريقة أسهل. على الرغم من هذه السهولة للإنترنت، إلا أنه قد تؤدي إلى العديد من التهديدات التي تتعلق بسرية محتويات الوسائط المنقولة مثل مصادقة الوسائط والتحقق من تكاملها.
Y. A. Hamza+2 more
semanticscholar +1 more source
An adaptive neuro‐fuzzy inference system is presented based on an optimization of genetic algorithm to classify normal and abnormal brain tumours. Abstract An adaptive neuro‐fuzzy inference system is presented which is optimized by a genetic algorithm to classify normal and abnormal brain tumours.
Marzieh Ghahramani, Nabiollah Shiri
wiley +1 more source
Deep learning‐based methods for detecting defects in cast iron parts and surfaces
First, this article used multiple data augmentation methods to alleviate the problem of small sample size in casting datasets. Second, attention mechanism was introduced. Finally, a novel feature fusion layer structure was adopted to improve the original network model.
Pengyu Wang, Peng Jing
wiley +1 more source
mBCCf: Multilevel Breast Cancer Classification Framework Using Radiomic Features
Breast cancer characterization remains a significant and challenging issue in contemporary medicine. Accurately distinguishing between malignant and benign breast lesions is crucial for effective diagnosis and treatment. The anatomical structure of malignant breast ultrasound images is more chaotic than that of benign images due to disease pathologies.
Lipismita Panigrahi+6 more
wiley +1 more source
Sparse Regularization Based on Orthogonal Tensor Dictionary Learning for Inverse Problems
In seismic data processing, data recovery including reconstruction of the missing trace and removal of noise from the recorded data are the key steps in improving the signal‐to‐noise ratio (SNR). The reconstruction of seismic data and removal of noise becomes a sparse optimization problem that can be solved by using sparse regularization.
Diriba Gemechu, Francisco Rossomando
wiley +1 more source
Multivariate $\alpha$-molecules
The suboptimal performance of wavelets with regard to the approximation of multivariate data gave rise to new representation systems, specifically designed for data with anisotropic features.
Flinth, Axel, Schäfer, Martin
core +1 more source
Compactly supported shearlets are optimally sparse
Cartoon-like images, i.e., C^2 functions which are smooth apart from a C^2 discontinuity curve, have by now become a standard model for measuring sparse (non-linear) approximation properties of directional representation systems. It was already shown that curvelets, contourlets, as well as shearlets do exhibit (almost) optimally sparse approximation ...
Gitta Kutyniok, Wang-Q Lim
openaire +3 more sources