[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] A review: Deep learning for medical image segmentation using multi-modality fusion
Multi-modality is widely used in medical imaging, because it can provide multiinformation
about a target (tumor, organ or tissue). Segmentation using multimodality consists of fusing …
about a target (tumor, organ or tissue). Segmentation using multimodality consists of fusing …
[HTML][HTML] COVID-19 image classification using deep features and fractional-order marine predators algorithm
Currently, we witness the severe spread of the pandemic of the new Corona virus, COVID-
19, which causes dangerous symptoms to humans and animals, its complications may lead …
19, which causes dangerous symptoms to humans and animals, its complications may lead …
Latent correlation representation learning for brain tumor segmentation with missing MRI modalities
Magnetic Resonance Imaging (MRI) is a widely used imaging technique to assess brain
tumor. Accurately segmenting brain tumor from MR images is the key to clinical diagnostics …
tumor. Accurately segmenting brain tumor from MR images is the key to clinical diagnostics …
A review on brain tumor segmentation of MRI images
The process of segmenting tumor from MRI image of a brain is one of the highly focused
areas in the community of medical science as MRI is noninvasive imaging. This paper …
areas in the community of medical science as MRI is noninvasive imaging. This paper …
MRI based medical image analysis: Survey on brain tumor grade classification
G Mohan, MM Subashini - Biomedical Signal Processing and Control, 2018 - Elsevier
A review on the recent segmentation and tumor grade classification techniques of brain
Magnetic Resonance (MR) Images is the objective of this paper. The requisite for early …
Magnetic Resonance (MR) Images is the objective of this paper. The requisite for early …
Lung cancer detection from CT image using improved profuse clustering and deep learning instantaneously trained neural networks
PM Shakeel, MA Burhanuddin, MI Desa - Measurement, 2019 - Elsevier
Automatic lung disease detection is a critical challenging task for researchers because of the
noise signals getting included into creative signals amid the image capturing process which …
noise signals getting included into creative signals amid the image capturing process which …
An integrated design of particle swarm optimization (PSO) with fusion of features for detection of brain tumor
Tumor in brain is a major cause of death in human beings. If not treated properly and timely,
there is a high chance of it to become malignant. Therefore, brain tumor detection at an …
there is a high chance of it to become malignant. Therefore, brain tumor detection at an …
Computer-aided diagnosis of human brain tumor through MRI: A survey and a new algorithm
ESA El-Dahshan, HM Mohsen, K Revett… - Expert systems with …, 2014 - Elsevier
Computer-aided detection/diagnosis (CAD) systems can enhance the diagnostic capabilities
of physicians and reduce the time required for accurate diagnosis. The objective of this …
of physicians and reduce the time required for accurate diagnosis. The objective of this …
A survey of MRI-based brain tumor segmentation methods
Brain tumor segmentation aims to separate the different tumor tissues such as active cells,
necrotic core, and edema from normal brain tissues of White Matter (WM), Gray Matter (GM) …
necrotic core, and edema from normal brain tissues of White Matter (WM), Gray Matter (GM) …