[HTML][HTML] Brain tumor detection and classification using machine learning: a comprehensive survey
J Amin, M Sharif, A Haldorai, M Yasmin… - Complex & intelligent …, 2022 - Springer
Brain tumor occurs owing to uncontrolled and rapid growth of cells. If not treated at an initial
phase, it may lead to death. Despite many significant efforts and promising outcomes in this …
phase, it may lead to death. Despite many significant efforts and promising outcomes in this …
[HTML][HTML] Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review
Autism spectrum disorder (ASD) is a brain condition characterized by diverse signs and
symptoms that appear in early childhood. ASD is also associated with communication …
symptoms that appear in early childhood. ASD is also associated with communication …
Deep convolutional neural networks with transfer learning for automated brain image classification
MR brain image categorization has been an active research domain from the last decade.
Several techniques have been devised in the past for MR image categorization, starting from …
Several techniques have been devised in the past for MR image categorization, starting from …
Brain tumor detection using statistical and machine learning method
Abstract Background and Objective Brain tumor occurs because of anomalous development
of cells. It is one of the major reasons of death in adults around the globe. Millions of deaths …
of cells. It is one of the major reasons of death in adults around the globe. Millions of deaths …
Automated brain image classification based on VGG-16 and transfer learning
The last few decades have witnessed active research in the domain of pathological brain
image classification starting from classical to the deep learning approaches like …
image classification starting from classical to the deep learning approaches like …
Brain tumor image segmentation via asymmetric/symmetric UNet based on two-pathway-residual blocks
M Aghalari, A Aghagolzadeh, M Ezoji - Biomedical signal processing and …, 2021 - Elsevier
Early diagnosis and selection of an appropriate treatment method will increase the survival
of cancer patients. Accurate and reliable brain tumor segmentation is an important …
of cancer patients. Accurate and reliable brain tumor segmentation is an important …
[HTML][HTML] An optimized XGBoost technique for accurate brain tumor detection using feature selection and image segmentation
CJ Tseng, C Tang - Healthcare Analytics, 2023 - Elsevier
An abnormal multiplication of cells in the brain forms malignant and benign brain tumors.
Malignant brain tumors are more prevalent than benign ones. Detecting a tumor's physical …
Malignant brain tumors are more prevalent than benign ones. Detecting a tumor's physical …
Tumor type detection in brain MR images of the deep model developed using hypercolumn technique, attention modules, and residual blocks
Brain cancer is a disease caused by the growth of abnormal aggressive cells in the brain
outside of normal cells. Symptoms and diagnosis of brain cancer cases are producing more …
outside of normal cells. Symptoms and diagnosis of brain cancer cases are producing more …
Arm-net: Attention-guided residual multiscale cnn for multiclass brain tumor classification using mr images
Brain tumor is the deadliest type of cancer and has the lowest survival rate when compared
with other cancers. Hence, timely detection of brain tumor is indispensable for patients to …
with other cancers. Hence, timely detection of brain tumor is indispensable for patients to …
Scale-adaptive super-feature based MetricUNet for brain tumor segmentation
Accurate segmentation of brain tumors is very essential for brain tumor diagnosis and
treatment plans. In general, brain tumor includes WT (whole tumor), TC (tumor core) and ET …
treatment plans. In general, brain tumor includes WT (whole tumor), TC (tumor core) and ET …