Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives
A brain tumor is an abnormal mass of tissue located inside the skull. In addition to putting
pressure on the healthy parts of the brain, it can lead to significant health problems …
pressure on the healthy parts of the brain, it can lead to significant health problems …
Artificial intelligence for cognitive health assessment: state-of-the-art, open challenges and future directions
The subjectivity and inaccuracy of in-clinic Cognitive Health Assessments (CHA) have led
many researchers to explore ways to automate the process to make it more objective and to …
many researchers to explore ways to automate the process to make it more objective and to …
Classifying brain tumors on magnetic resonance imaging by using convolutional neural networks
MA Gómez-Guzmán, L Jiménez-Beristaín… - Electronics, 2023 - mdpi.com
The study of neuroimaging is a very important tool in the diagnosis of central nervous system
tumors. This paper presents the evaluation of seven deep convolutional neural network …
tumors. This paper presents the evaluation of seven deep convolutional neural network …
[HTML][HTML] Robust clinical applicable CNN and U-Net based algorithm for MRI classification and segmentation for brain tumor
A Akter, N Nosheen, S Ahmed, M Hossain… - Expert Systems with …, 2024 - Elsevier
Early diagnosis of brain tumors is critical for enhancing patient prognosis and treatment
options, while accurate classification and segmentation of brain tumors are vital for …
options, while accurate classification and segmentation of brain tumors are vital for …
Pixel-level fusion approach with vision transformer for early detection of Alzheimer's disease
Alzheimer's disease (AD) has become a serious hazard to human health in recent years,
and proper screening and diagnosis of AD remain a challenge. Multimodal neuroimaging …
and proper screening and diagnosis of AD remain a challenge. Multimodal neuroimaging …
Brain tumor segmentation based on optimized convolutional neural network and improved chimp optimization algorithm
Reliable and accurate brain tumor segmentation is a challenging task even with the
appropriate acquisition of brain images. Tumor grading and segmentation utilizing Magnetic …
appropriate acquisition of brain images. Tumor grading and segmentation utilizing Magnetic …
Hybrid‐NET: A fusion of DenseNet169 and advanced machine learning classifiers for enhanced brain tumor diagnosis
The computer‐aided diagnostic (CAD) method to detect human brain tumors relies heavily
on automated tumor characterization. Although CAD method has been extensively …
on automated tumor characterization. Although CAD method has been extensively …
Crossover smell agent optimized multilayer perceptron for precise brain tumor classification on MRI images
M Arumugam, A Thiyagarajan, L Adhi… - Expert Systems with …, 2024 - Elsevier
The Brain tumor is considered an unusual growth of cells in the nervous system that restricts
the normal functionality of the brain. However, is generated in the skull and pressures the …
the normal functionality of the brain. However, is generated in the skull and pressures the …
ResUNet+: A new convolutional and attention block-based approach for brain tumor segmentation
The number of brain tumor cases has increased in recent years. Therefore, accurate
diagnosis and treatment of brain tumors are extremely important. Accurate detection of tumor …
diagnosis and treatment of brain tumors are extremely important. Accurate detection of tumor …
SkinNet‐ENDO: Multiclass skin lesion recognition using deep neural network and Entropy‐Normal distribution optimization algorithm with ELM
The early diagnosis of skin cancer through clinical methods reduces the human mortality
rate. The manual screening of dermoscopic images is not an efficient procedure; therefore …
rate. The manual screening of dermoscopic images is not an efficient procedure; therefore …