Gan-tl: Generative adversarial networks with transfer learning for mri reconstruction

M Yaqub, F **chao, S Ahmed, K Arshid, MA Bilal… - Applied Sciences, 2022 - mdpi.com
Generative adversarial networks (GAN), which are fueled by deep learning, are an efficient
technique for image reconstruction using under-sampled MR data. In most cases, the …

Enhancing healthcare recommendation: transfer learning in deep convolutional neural networks for Alzheimer disease detection

PK Pandey, J Pruthi, S Alzahrani, A Verma… - Frontiers in …, 2024 - frontiersin.org
Neurodegenerative disorders such as Alzheimer's Disease (AD) and Mild Cognitive
Impairment (MCI) significantly impact brain function and cognition. Advanced neuroimaging …

Automatic Skull Strip** Using Multidimensional Multi-input Multi-output U-Net Model for Alzheimer's Disease

P Gautam, M Singh - Applied Magnetic Resonance, 2024 - Springer
Skull strip** is a fundamental step in analyzing magnetic resonance imaging (MRI) scans,
which play a crucial role in disease diagnosis such as Alzheimer's disease (AD). Alzheimer's …

Efficient MRI image enhancement by improved denoising techniques for better skull strip** using attention module-based convolution neural network

J Jeme V, A Jerome S - Computer Methods in Biomechanics and …, 2024 - Taylor & Francis
Anatomical structure preservation throughout the denoising process is a challenge in the
domain of medical imaging. The Rician noise introduced through the acquisition procedure …

Classification, Regression and Segmentation directly from k-Space in Cardiac MRI

R Li, J Pan, Y Zhu, J Ni, D Rueckert - International Workshop on Machine …, 2024 - Springer
Abstract Cardiac Magnetic Resonance Imaging (CMR) is the gold standard for diagnosing
cardiovascular diseases. Clinical diagnoses predominantly rely on magnitude-only Digital …

Tumor likelihood estimation on MRI prostate data by utilizing k-Space information

M Rempe, F Hörst, C Seibold, B Hadaschik… - arxiv preprint arxiv …, 2024 - arxiv.org
We present a novel preprocessing and prediction pipeline for the classification of magnetic
resonance imaging (MRI) that takes advantage of the information rich complex valued k …

Direct Cardiac Segmentation from Undersampled K-space Using Transformers

Y Zhang, N Stolt-Ansó, J Pan, W Huang… - arxiv preprint arxiv …, 2024 - arxiv.org
The prevailing deep learning-based methods of predicting cardiac segmentation involve
reconstructed magnetic resonance (MR) images. The heavy dependency of segmentation …

Methods of Brain Extraction from Magnetic Resonance Images of Human Head: A Review

S Praveenkumar, T Kalaiselvi… - Critical Reviews™ in …, 2023 - dl.begellhouse.com
Medical images are providing vital information to aid physicians in diagnosing a disease
afflicting the organ of a human body. Magnetic resonance imaging is an important imaging …

and Mild Cognitive Impairment: Leveraging Advanced Preprocessing

PK Pandey, J Pruthi, SB Khan - Proceedings of Fifth International …, 2024 - books.google.com
Alzheimer's disease (AD) and moderate cognitive impairment (MCI) are neurodegenerative
disorders that cause significant impairment in brain function. This study examines the …

Enhanced Detection of Alzheimer's and Mild Cognitive Impairment: Leveraging Advanced Preprocessing and Convolutional Neural Networks

PK Pandey, J Pruthi, SB Khan - International Conference on Cognitive …, 2023 - Springer
Alzheimer's disease (AD) and moderate cognitive impairment (MCI) are neurodegenerative
disorders that cause significant impairment in brain function. This study examines the …