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 …
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 brain tumor classification using ensemble of deep features and machine learning classifiers
Brain tumor classification plays an important role in clinical diagnosis and effective
treatment. In this work, we propose a method for brain tumor classification using an …
treatment. In this work, we propose a method for brain tumor classification using an …
[HTML][HTML] Accurate brain tumor detection using deep convolutional neural network
Detection and Classification of a brain tumor is an important step to better understanding its
mechanism. Magnetic Reasoning Imaging (MRI) is an experimental medical imaging …
mechanism. Magnetic Reasoning Imaging (MRI) is an experimental medical imaging …
Multi-grade brain tumor classification using deep CNN with extensive data augmentation
Numerous computer-aided diagnosis (CAD) systems have been recently presented in the
history of medical imaging to assist radiologists about their patients. For full assistance of …
history of medical imaging to assist radiologists about their patients. For full assistance of …
Tuberculosis disease diagnosis based on an optimized machine learning model
Computer science plays an important role in modern dynamic health systems. Given the
collaborative nature of the diagnostic process, computer technology provides important …
collaborative nature of the diagnostic process, computer technology provides important …
Deep learning based enhanced tumor segmentation approach for MR brain images
Automation in medical industry has become one of the necessities in today's medical
scenario. Radiologists/physicians need such automation techniques for accurate diagnosis …
scenario. Radiologists/physicians need such automation techniques for accurate diagnosis …
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 …
Spatiotemporal forecasting in earth system science: Methods, uncertainties, predictability and future directions
Spatiotemporal forecasting (STF) extends traditional time series forecasting or spatial
interpolation problem to space and time dimensions. Here, we review the statistical, physical …
interpolation problem to space and time dimensions. Here, we review the statistical, physical …
ERV-Net: An efficient 3D residual neural network for brain tumor segmentation
Brain tumors are the most aggressive and mortal cancers, which lead to short life
expectancy. A reliable and efficient automatic or semi-automatic segmentation method is …
expectancy. A reliable and efficient automatic or semi-automatic segmentation method is …