On the application of deep learning and multifractal techniques to classify emotions and instruments using Indian Classical Music
Music is often considered as the language of emotions. The way it stimulates the emotional
appraisal across people from different communities, culture and demographics has long …
appraisal across people from different communities, culture and demographics has long …
Decomposition-based variational network for multi-contrast MRI super-resolution and reconstruction
Multi-contrast MRI super-resolution (SR) and reconstruction methods aim to explore
complementary information from the reference image to help the reconstruction of the target …
complementary information from the reference image to help the reconstruction of the target …
Dual-domain accelerated MRI reconstruction using transformers with learning-based undersampling
Acceleration in MRI has garnered much attention from the deep-learning community in
recent years, particularly for imaging large anatomical volumes such as the abdomen or …
recent years, particularly for imaging large anatomical volumes such as the abdomen or …
Deep unfolding convolutional dictionary model for multi-contrast MRI super-resolution and reconstruction
Magnetic resonance imaging (MRI) tasks often involve multiple contrasts. Recently,
numerous deep learning-based multi-contrast MRI super-resolution (SR) and reconstruction …
numerous deep learning-based multi-contrast MRI super-resolution (SR) and reconstruction …
Joint Under-Sampling Pattern and Dual-Domain Reconstruction for Accelerating Multi-Contrast MRI
Multi-Contrast Magnetic Resonance Imaging (MCMRI) utilizes the short-time reference
image to facilitate the reconstruction of the long-time target one, providing a new solution for …
image to facilitate the reconstruction of the long-time target one, providing a new solution for …
Global k-space interpolation for dynamic mri reconstruction using masked image modeling
Abstract In dynamic Magnetic Resonance Imaging (MRI), k-space is typically undersampled
due to limited scan time, resulting in aliasing artifacts in the image domain. Hence, dynamic …
due to limited scan time, resulting in aliasing artifacts in the image domain. Hence, dynamic …
FEFA: Frequency Enhanced Multi-Modal MRI Reconstruction with Deep Feature Alignment
Integrating complementary information from multiple magnetic resonance imaging (MRI)
modalities is often necessary to make accurate and reliable diagnostic decisions. However …
modalities is often necessary to make accurate and reliable diagnostic decisions. However …
Progressive Divide-and-Conquer via Subsampling Decomposition for Accelerated MRI
Deep unfolding networks (DUN) have emerged as a popular iterative framework for
accelerated magnetic resonance imaging (MRI) reconstruction. However conventional DUN …
accelerated magnetic resonance imaging (MRI) reconstruction. However conventional DUN …
Frequency Learning via Multi-Scale Fourier Transformer for MRI Reconstruction
Since Magnetic Resonance Imaging (MRI) requires a long acquisition time, various methods
were proposed to reduce the time, but they ignored the frequency information and non-local …
were proposed to reduce the time, but they ignored the frequency information and non-local …
Accelerated MRI reconstructions via variational network and feature domain learning
We introduce three architecture modifications to enhance the performance of the end-to-end
(E2E) variational network (VarNet) for undersampled MRI reconstructions. We first …
(E2E) variational network (VarNet) for undersampled MRI reconstructions. We first …