Brain tumor segmentation and classification from magnetic resonance images: Review of selected methods from 2014 to 2019
The past few years have witnessed a significant increase in medical cases related to brain
tumors, making it the 10th most common form of tumor affecting children and adults alike …
tumors, making it the 10th most common form of tumor affecting children and adults alike …
A comprehensive survey on brain tumor diagnosis using deep learning and emerging hybrid techniques with multi-modal MR image
The brain tumor is considered the deadly disease of the century. At present, neuroscience
and artificial intelligence conspire in the timely delineation, detection, and classification of …
and artificial intelligence conspire in the timely delineation, detection, and classification of …
Quantum machine learning architecture for COVID-19 classification based on synthetic data generation using conditional adversarial neural network
Background COVID-19 is a novel virus that affects the upper respiratory tract, as well as the
lungs. The scale of the global COVID-19 pandemic, its spreading rate, and deaths are …
lungs. The scale of the global COVID-19 pandemic, its spreading rate, and deaths are …
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 …
Memory, evolutionary operator, and local search based improved Grey Wolf Optimizer with linear population size reduction technique
Optimization of multi-modal functions is challenging even for evolutionary and swarm-based
algorithms as it requires an efficient exploration for finding the promising region of the …
algorithms as it requires an efficient exploration for finding the promising region of the …
An improved framework for brain tumor analysis using MRI based on YOLOv2 and convolutional neural network
Brain tumor is a group of anomalous cells. The brain is enclosed in a more rigid skull. The
abnormal cell grows and initiates a tumor. Detection of tumor is a complicated task due to …
abnormal cell grows and initiates a tumor. Detection of tumor is a complicated task due to …
A survey on brain tumor detection techniques for MR images
PK Chahal, S Pandey, S Goel - Multimedia Tools and Applications, 2020 - Springer
One of the most crucial tasks in any brain tumor detection system is the isolation of abnormal
tissues from normal brain tissues. Interestingly, domain of brain tumor analysis has …
tissues from normal brain tissues. Interestingly, domain of brain tumor analysis has …
[图书][B] Computer Vision and Recognition Systems: Research Innovations and Trends
This cutting-edge volume, Computer Vision and Recognition Systems: Research
Innovations and Trends, focuses on how artificial intelligence can be used to give computers …
Innovations and Trends, focuses on how artificial intelligence can be used to give computers …
Particle swarm optimization and two-way fixed-effects analysis of variance for efficient brain tumor segmentation
Simple Summary Segmentation of brain tumor images from magnetic resonance imaging
(MRI) is a challenging topic in medical image analysis. The brain tumor can take many …
(MRI) is a challenging topic in medical image analysis. The brain tumor can take many …
Investigating brain tumor segmentation and detection techniques
Brain tumor is a life-threatening problem and hampers the normal functioning of the human
body. For proper diagnosis and efficient treatment planning, it is necessary to detect the …
body. For proper diagnosis and efficient treatment planning, it is necessary to detect the …