Emerging trends in fast MRI using deep-learning reconstruction on undersampled k-space data: a systematic review
Magnetic Resonance Imaging (MRI) is an essential medical imaging modality that provides
excellent soft-tissue contrast and high-resolution images of the human body, allowing us to …
excellent soft-tissue contrast and high-resolution images of the human body, allowing us to …
A review of spatial enhancement of hyperspectral remote sensing imaging techniques
N Aburaed, MQ Alkhatib, S Marshall… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Remote sensing technology has undeniable importance in various industrial applications,
such as mineral exploration, plant detection, defect detection in aerospace and shipbuilding …
such as mineral exploration, plant detection, defect detection in aerospace and shipbuilding …
Research on image super-resolution reconstruction mechanism based on convolutional neural network
Super-resolution reconstruction techniques entail the utilization of software algorithms to
transform one or more sets of low-resolution images captured from the same scene into high …
transform one or more sets of low-resolution images captured from the same scene into high …
[HTML][HTML] A hybrid approach for melanoma classification using ensemble machine learning techniques with deep transfer learning
Abstract Generally, Melanoma, Merkel cell cancer, Squamous cell carcinoma, and Basal cell
carcinoma, are the four major categories of skin cancers. In contrast to other cancer types …
carcinoma, are the four major categories of skin cancers. In contrast to other cancer types …
[HTML][HTML] Predicting progression of Alzheimer's disease using forward-to-backward bi-directional network with integrative imputation
If left untreated, Alzheimer's disease (AD) is a leading cause of slowly progressive dementia.
Therefore, it is critical to detect AD to prevent its progression. In this study, we propose a …
Therefore, it is critical to detect AD to prevent its progression. In this study, we propose a …
Lung_PAYNet: a pyramidal attention based deep learning network for lung nodule segmentation
Accurate and reliable lung nodule segmentation in computed tomography (CT) images is
required for early diagnosis of lung cancer. Some of the difficulties in detecting lung nodules …
required for early diagnosis of lung cancer. Some of the difficulties in detecting lung nodules …
De-aliasing and accelerated sparse magnetic resonance image reconstruction using fully dense CNN with attention gates
When sparsely sampled data are used to accelerate magnetic resonance imaging (MRI),
conventional reconstruction approaches produce significant artifacts that obscure the …
conventional reconstruction approaches produce significant artifacts that obscure the …
Artificial intelligence in adolescents mental health disorder diagnosis, prognosis, and treatment
Social, psychological, and emotional wellbeing are all considered to be components of
one's mental health. It affects how someone thinks, feels, and responds to circumstances …
one's mental health. It affects how someone thinks, feels, and responds to circumstances …
[HTML][HTML] Clinical evaluation of super-resolution for brain MRI images based on generative adversarial networks
Y Terada, T Miyasaka, A Nakao, S Funayama… - Informatics in Medicine …, 2022 - Elsevier
In magnetic resonance imaging (MRI), reducing long scan times is an urgent issue that
could be addressed with super-resolution (SR) techniques. Most of the SR networks using …
could be addressed with super-resolution (SR) techniques. Most of the SR networks using …
[HTML][HTML] Drug-disease association prediction based on end-to-end multi-layer heterogeneous graph convolutional encoders
S Ghasemi, A Lakizadeh - Informatics in Medicine Unlocked, 2023 - Elsevier
Traditional drug development in wet labs has long been a costly, cumbersome and error-
prone process. Thus, taking advantage of computational power to create algorithmic …
prone process. Thus, taking advantage of computational power to create algorithmic …