Deep learning for smart Healthcare—A survey on brain tumor detection from medical imaging
M Arabahmadi, R Farahbakhsh, J Rezazadeh - Sensors, 2022 - mdpi.com
Advances in technology have been able to affect all aspects of human life. For example, the
use of technology in medicine has made significant contributions to human society. In this …
use of technology in medicine has made significant contributions to human society. In this …
Role of deep learning in brain tumor detection and classification (2015 to 2020): A review
During the last decade, computer vision and machine learning have revolutionized the world
in every way possible. Deep Learning is a sub field of machine learning that has shown …
in every way possible. Deep Learning is a sub field of machine learning that has shown …
Brain tumor detection based on deep learning approaches and magnetic resonance imaging
Simple Summary In this research, we addressed the challenging task of brain tumor
detection in MRI scans using a large collection of brain tumor images. We demonstrated that …
detection in MRI scans using a large collection of brain tumor images. We demonstrated that …
Deep learning based brain tumor segmentation: a survey
Brain tumor segmentation is one of the most challenging problems in medical image
analysis. The goal of brain tumor segmentation is to generate accurate delineation of brain …
analysis. The goal of brain tumor segmentation is to generate accurate delineation of brain …
Brain tumor detection and classification using deep learning and sine-cosine fitness grey wolf optimization
Diagnosing a brain tumor takes a long time and relies heavily on the radiologist's abilities
and experience. The amount of data that must be handled has increased dramatically as the …
and experience. The amount of data that must be handled has increased dramatically as the …
[HTML][HTML] Brain tumor detection in MR image using superpixels, principal component analysis and template based K-means clustering algorithm
In the present era, human brain tumor is the extremist dangerous and devil to the human
being that leads to certain death. Furthermore, the brain tumor arises more complexity of …
being that leads to certain death. Furthermore, the brain tumor arises more complexity of …
[PDF][PDF] Brain tumor classification using convolutional neural networks
J Seetha, SS Raja - Biomedical & Pharmacology Journal, 2018 - academia.edu
The brain tumors, are the most common and aggressive disease, leading to a very short life
expectancy in their highest grade. Thus, treatment planning is a key stage to improve the …
expectancy in their highest grade. Thus, treatment planning is a key stage to improve the …
Automatic brain tumor segmentation using cascaded anisotropic convolutional neural networks
A cascade of fully convolutional neural networks is proposed to segment multi-modal
Magnetic Resonance (MR) images with brain tumor into background and three hierarchical …
Magnetic Resonance (MR) images with brain tumor into background and three hierarchical …
Image analysis for MRI based brain tumor detection and feature extraction using biologically inspired BWT and SVM
The segmentation, detection, and extraction of infected tumor area from magnetic resonance
(MR) images are a primary concern but a tedious and time taking task performed by …
(MR) images are a primary concern but a tedious and time taking task performed by …
A survey on U-shaped networks in medical image segmentations
The U-shaped network is one of the end-to-end convolutional neural networks (CNNs). In
electron microscope segmentation of ISBI challenge 2012, the concise architecture and …
electron microscope segmentation of ISBI challenge 2012, the concise architecture and …