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 …
Machine learning and deep learning approaches for brain disease diagnosis: principles and recent advances
Brain is the controlling center of our body. With the advent of time, newer and newer brain
diseases are being discovered. Thus, because of the variability of brain diseases, existing …
diseases are being discovered. Thus, because of the variability of brain diseases, existing …
[HTML][HTML] 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 …
[HTML][HTML] Brain tumor detection and classification on MR images by a deep wavelet auto-encoder model
I Abd El Kader, G Xu, Z Shuai, S Saminu, I Javaid… - diagnostics, 2021 - mdpi.com
The process of diagnosing brain tumors is very complicated for many reasons, including the
brain's synaptic structure, size, and shape. Machine learning techniques are employed to …
brain's synaptic structure, size, and shape. Machine learning techniques are employed to …
Brain tumor detection based on hybrid deep neural network in MRI by adaptive squirrel search optimization
D Deb, S Roy - Multimedia tools and applications, 2021 - Springer
In the medical field, image segmentation is a paramount and challenging task. The head
and vertebral column make up the central nervous system (CNS), which control all the …
and vertebral column make up the central nervous system (CNS), which control all the …
[HTML][HTML] A review on computer aided diagnosis of acute brain stroke
Amongst the most common causes of death globally, stroke is one of top three affecting over
100 million people worldwide annually. There are two classes of stroke, namely ischemic …
100 million people worldwide annually. There are two classes of stroke, namely ischemic …
Computational methods for automated mitosis detection in histopathology images: A review
Mitosis detection is an important step in pathology procedures in the context of cancer
diagnosis and prognosis. Prevalent process for this task is by manually observing …
diagnosis and prognosis. Prevalent process for this task is by manually observing …
The cluster analysis and feature selection: Perspective of machine learning and image processing
A Behura - Data Analytics in Bioinformatics: A Machine …, 2021 - Wiley Online Library
Medical Imaging is the process of producing visible images of inner structures of the body for
scientific and medicinal study and treatment as well as visible view of the function of interior …
scientific and medicinal study and treatment as well as visible view of the function of interior …
Diagnosis of COVID-19 infection using three-dimensional semantic segmentation and classification of computed tomography images
Abstract Coronavirus 19 (COVID-19) can cause severe pneumonia that may be fatal. Correct
diagnosis is essential. Computed tomography (CT) usefully detects symptoms of COVID-19 …
diagnosis is essential. Computed tomography (CT) usefully detects symptoms of COVID-19 …
Brain tumour classification using siamese neural network and neighbourhood analysis in embedded feature space
The application of deep transfer learning techniques has been successful in developing
accurate systems for brain tumour classification on large‐scale medical image databases …
accurate systems for brain tumour classification on large‐scale medical image databases …