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Existing and emerging breast cancer detection technologies and its challenges: a review
Breast cancer is the most leading cancer occurring in women and is a significant factor in
female mortality. Early diagnosis of breast cancer with Artificial Intelligent (AI) developments …
female mortality. Early diagnosis of breast cancer with Artificial Intelligent (AI) developments …
Usefulness of deep learning-based noise reduction for 1.5 T MRI brain images
AIM To evaluate 1.5 T magnetic resonance imaging (MRI) brain images with denoising
procedures using deep learning-based reconstruction (dDLR) relative to the original 1.5 and …
procedures using deep learning-based reconstruction (dDLR) relative to the original 1.5 and …
[HTML][HTML] Improving structural MRI preprocessing with hybrid transformer GANs
Magnetic resonance imaging (MRI) is a technique that is widely used in practice to evaluate
any pathologies in the human body. One of the areas of interest is the human brain …
any pathologies in the human body. One of the areas of interest is the human brain …
[HTML][HTML] Image Synthesis in Nuclear Medicine Imaging with Deep Learning: A Review
Nuclear medicine imaging (NMI) is essential for the diagnosis and sensing of various
diseases; however, challenges persist regarding image quality and accessibility during NMI …
diseases; however, challenges persist regarding image quality and accessibility during NMI …
Classification and Diagnosis of Alzheimer's Disease based on a combination of Deep Features and Machine Learning
M Saim, F Amel - 2022 7th International Conference on Image …, 2022 - ieeexplore.ieee.org
Alzheimer's disease (AD) is a neurodegenerative illness that causes structural changes in
the brain over time. Furthermore, various symptoms, most notably memory disorder, relate to …
the brain over time. Furthermore, various symptoms, most notably memory disorder, relate to …
A genetic programming Rician noise reduction and explainable deep learning model for Alzheimer's diseases severity prediction
Background: Degradation of magnetic resonance imaging (MRI) remains a challenging
issue, with noise being a key damaging component introduced due to a variety of …
issue, with noise being a key damaging component introduced due to a variety of …
3DCC-MPNN: automated 3D reconstruction of corpus callosum based on modified PNN and marching cubes
The present study addresses the segmentation and the 3D reconstruction of the corpus
callosum from MRI scans. Accurate segmentation of the corpus callosum is essential in …
callosum from MRI scans. Accurate segmentation of the corpus callosum is essential in …
Automated alzheimer's disease detection and diagnosis method based on Bayesian optimization and CNN-based pre-trained features
M Saim, A Feroui - Multimedia Tools and Applications, 2024 - Springer
Alzheimer's disease (AD) is a prevalent neurodegenerative disorder characterized by
progressive cognitive decline, making early diagnosis crucial for effective intervention …
progressive cognitive decline, making early diagnosis crucial for effective intervention …
Haptic‐based virtual reality simulator for lateral ventricle puncture operation
XH Su, Z Deng, BW He, YQ Liu - The International Journal of …, 2020 - Wiley Online Library
Background The implementation of lateral ventricle puncture (LVP) operation is challenging
due to the complex anatomy structure of human brains. Surgical simulator has been proved …
due to the complex anatomy structure of human brains. Surgical simulator has been proved …
Automated quality control of small animal MR neuroimaging data
Magnetic resonance imaging (MRI) is a valuable tool for studying brain structure and
function in animal and clinical studies. With the growth of public MRI repositories, access to …
function in animal and clinical studies. With the growth of public MRI repositories, access to …