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 …
A survey of brain tumor segmentation and classification algorithms
A brain Magnetic resonance imaging (MRI) scan of a single individual consists of several
slices across the 3D anatomical view. Therefore, manual segmentation of brain tumors from …
slices across the 3D anatomical view. Therefore, manual segmentation of brain tumors from …
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 …
Magnetic resonance image-based brain tumour segmentation methods: A systematic review
JM Bhalodiya, SN Lim Choi Keung… - Digital Health, 2022 - journals.sagepub.com
Background Image segmentation is an essential step in the analysis and subsequent
characterisation of brain tumours through magnetic resonance imaging. In the literature …
characterisation of brain tumours through magnetic resonance imaging. In the literature …
Detection of brain tumor in 3D MRI images using local binary patterns and histogram orientation gradient
S Abbasi, F Tajeripour - Neurocomputing, 2017 - Elsevier
Brain tumor pathology is one of the most common mortality issues considered as an
essential priority for health care societies. Accurate diagnosis of the type of disorder is …
essential priority for health care societies. Accurate diagnosis of the type of disorder is …
A unified patch based method for brain tumor detection using features fusion
M Sharif, J Amin, MW Nisar, MA Anjum… - Cognitive Systems …, 2020 - Elsevier
The manuscript authenticates the effectiveness of fusing texture and geometrical (GEO)
features in magnetic resonance imaging (MRI) for tumor classification. The presented …
features in magnetic resonance imaging (MRI) for tumor classification. The presented …
Generative adversarial networks for brain lesion detection
V Alex, MS KP, SS Chennamsetty… - … Imaging 2017: Image …, 2017 - spiedigitallibrary.org
Manual segmentation of brain lesions from Magnetic Resonance Images (MRI) is
cumbersome and introduces errors due to inter-rater variability. This paper introduces a …
cumbersome and introduces errors due to inter-rater variability. This paper introduces a …
Brain tumor segmentation in multimodal MRI images using novel LSIS operator and deep learning
Determination of tumor extent is the foremost challenge in the brain tumor treatment
planning and valuation. Among various conventional anatomical imaging techniques for …
planning and valuation. Among various conventional anatomical imaging techniques for …
Automated brain tumor segmentation based on multi-planar superpixel level features extracted from 3D MR images
Brain tumor segmentation from Magnetic Resonance Imaging (MRI) is of great importance
for better tumor diagnosis, growth rate prediction and radiotherapy planning. But this task is …
for better tumor diagnosis, growth rate prediction and radiotherapy planning. But this task is …
On hierarchical brain tumor segmentation in MRI using fully convolutional neural networks: a preliminary study
Magnetic Resonance Imaging is the preferred imaging modality for assessing brain tumors,
and segmentation is necessary for diagnosis and treatment planning. Thus, robust automatic …
and segmentation is necessary for diagnosis and treatment planning. Thus, robust automatic …