Deep Learning Archives

May 2, 2024

Neuromelanin-MRI using 2D GRE and deep learning: considerations for improving the visualization of substantia nigra and locus coeruleus

https://arxiv.org/ftp/arxiv/papers/2306/2306.16315.pdf Authors Published Date: 2023-06

May 2, 2024

An untrained deep learning method for reconstructing dynamic MR images from accelerated model-based data

https://onlinelibrary.wiley.com/doi/10.1002/mrm.29547 Authors Published Date: 2022-12

May 2, 2024

Using Minimally-Invasive IN VIVO Imaging to Map the Genomic Heterogeneity of Human Brain Tumors

https://hammer.purdue.edu/articles/thesis/_b_Using_Minimally-Invasive_b_b_i_In_vivo_i_b_b_Imaging_to_Map_the_Genomic_Heterogeneity_of_Human_Brain_Tumors_b_/25648500 Authors Published Date: 2024-05

April 17, 2024

Reduction of ADC bias in diffusion MRI with deep learning-based acceleration: A phantom validation study at 3.0 T

https://www.sciencedirect.com/science/article/pii/S0730725X24001310 Authors [/author] Published Date: 2024-04 CaliberMRI Reference Library content, paper, article, journal, etc. published 2024-04

October 19, 2023

Clinical feasibility of deep learning reconstruction in liver diffusion-weighted imaging: Improvement of image quality and impact on apparent diffusion coefficient value

https://www.ejradiology.com/article/S0720-048X(23)00463-1/fulltext Published Date: 2023-10

Neuromelanin-MRI using 2D GRE and deep learning: considerations for improving the visualization of substantia nigra and locus coeruleus

An untrained deep learning method for reconstructing dynamic MR images from accelerated model-based data

Using Minimally-Invasive IN VIVO Imaging to Map the Genomic Heterogeneity of Human Brain Tumors

Reduction of ADC bias in diffusion MRI with deep learning-based acceleration: A phantom validation study at 3.0 T

Clinical feasibility of deep learning reconstruction in liver diffusion-weighted imaging: Improvement of image quality and impact on apparent diffusion coefficient value

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Neuromelanin-MRI using 2D GRE and deep learning: considerations for improving the visualization of substantia nigra and locus coeruleus

An untrained deep learning method for reconstructing dynamic MR images from accelerated model-based data

Using Minimally-Invasive IN VIVO Imaging to Map the Genomic Heterogeneity of Human Brain Tumors

Reduction of ADC bias in diffusion MRI with deep learning-based acceleration: A phantom validation study at 3.0 T

Clinical feasibility of deep learning reconstruction in liver diffusion-weighted imaging: Improvement of image quality and impact on apparent diffusion coefficient value

Reduction of ADC bias in diffusion MRI with deep learning-based acceleration: A phantom validation study at 3.0 T