Artificial intelligence in brain tumor detection through MRI scans: advancements and challenges
A brain tumor is one of the most perilous diseases in human beings. The manual
segmentation of brain tumors is costly and takes a lot of time; due to this reason, automated …
segmentation of brain tumors is costly and takes a lot of time; due to this reason, automated …
A customized VGG19 network with concatenation of deep and handcrafted features for brain tumor detection
Brain tumor (BT) is one of the brain abnormalities which arises due to various reasons. The
unrecognized and untreated BT will increase the morbidity and mortality rates. The clinical …
unrecognized and untreated BT will increase the morbidity and mortality rates. The clinical …
Social group optimization–assisted Kapur's entropy and morphological segmentation for automated detection of COVID-19 infection from computed tomography …
Abstract The coronavirus disease (COVID-19) caused by a novel coronavirus, SARS-CoV-2,
has been declared a global pandemic. Due to its infection rate and severity, it has emerged …
has been declared a global pandemic. Due to its infection rate and severity, it has emerged …
A systematic study of artificial intelligence-based methods for detecting brain tumors
The brain is regarded as one of the most effective body-controlling organs. The development
of technology has enabled the early and accurate detection of brain tumors, which makes a …
of technology has enabled the early and accurate detection of brain tumors, which makes a …
Automated segmentation of leukocyte from hematological images—a study using various CNN schemes
Medical images play a fundamental role in disease screening, and automated evaluation of
these images is widely preferred in hospitals. Recently, Convolutional Neural Network …
these images is widely preferred in hospitals. Recently, Convolutional Neural Network …
Convolutional-neural-network assisted segmentation and SVM classification of brain tumor in clinical MRI slices
Due to the increased disease occurrence rates in humans, the need for the Automated
Disease Diagnosis (ADD) systems is also raised. Most of the ADD systems are proposed to …
Disease Diagnosis (ADD) systems is also raised. Most of the ADD systems are proposed to …
Computational Intelligence and Metaheuristic Techniques for Brain Tumor Detection through IoMT‐Enabled MRI Devices
The brain tumor is the 22nd most common cancer worldwide, with 1.8% of new cancers. It is
likely the most severe ailment that necessitates early discovery and treatment, and it …
likely the most severe ailment that necessitates early discovery and treatment, and it …
Evaluation of brain tumor using brain MRI with modified-moth-flame algorithm and Kapur's thresholding: A study
S Kadry, V Rajinikanth, NSM Raja… - Evolutionary …, 2021 - Springer
Brain abnormality is a severe illness in humans. An unrecognised and untreated brain
illness will lead to a lot of complications despite of gender and age. Brain tumor is one of the …
illness will lead to a lot of complications despite of gender and age. Brain tumor is one of the …
An improved method for diagnosis of Parkinson's disease using deep learning models enhanced with metaheuristic algorithm
Parkinson's disease (PD) is challenging for clinicians to accurately diagnose in the early
stages. Quantitative measures of brain health can be obtained safely and non-invasively …
stages. Quantitative measures of brain health can be obtained safely and non-invasively …
Detecting epilepsy in EEG signals using synchro-extracting-transform (SET) supported classification technique
Epilepsy is one of the medical conditions in human caused by the disorder in central-
nervous-system (CNS). Early detection and treatment are essential patient healthcare. Brain …
nervous-system (CNS). Early detection and treatment are essential patient healthcare. Brain …