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 …
Classification of brain tumor from magnetic resonance imaging using vision transformers ensembling
The automated classification of brain tumors plays an important role in supporting
radiologists in decision making. Recently, vision transformer (ViT)-based deep neural …
radiologists in decision making. Recently, vision transformer (ViT)-based deep neural …
A comprehensive review of analyzing the chest X-ray images to detect COVID-19 infections using deep learning techniques
K Subramaniam, N Palanisamy, RA Sinnaswamy… - Soft computing, 2023 - Springer
COVID-19, a highly infectious respiratory disease a used by SARS virus, has killed millions
of people across many countries. To enhance quick and accurate diagnosis of COVID-19 …
of people across many countries. To enhance quick and accurate diagnosis of COVID-19 …
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 …
Efficient brain tumor segmentation using OTSU and K-means clustering in homomorphic transform
In computer vision, image segmentation technology plays a vital role in computer-aided
diagnostic systems to precisely and accurately identify the area to be treated. Practically, it is …
diagnostic systems to precisely and accurately identify the area to be treated. Practically, it is …
Brain tumor segmentation in multimodal MRI images using novel LSIS operator and deep learning
Determination of tumor extent is the foremost challenge in the brain tumor treatment
planning and valuation. Among various conventional anatomical imaging techniques for …
planning and valuation. Among various conventional anatomical imaging techniques for …
UniVisNet: A unified visualization and classification network for accurate grading of gliomas from MRI
Y Zheng, D Huang, X Hao, J Wei, H Lu, Y Liu - Computers in Biology and …, 2023 - Elsevier
Accurate grading of brain tumors plays a crucial role in the diagnosis and treatment of
glioma. While convolutional neural networks (CNNs) have shown promising performance in …
glioma. While convolutional neural networks (CNNs) have shown promising performance in …
A computer-aided diagnosis system for brain tumors based on artificial intelligence algorithms
The choice of treatment and prognosis evaluation depend on the accurate early diagnosis of
brain tumors. Many brain tumors go undiagnosed or are overlooked by clinicians as a result …
brain tumors. Many brain tumors go undiagnosed or are overlooked by clinicians as a result …
A distance transformation deep forest framework with hybrid-feature fusion for cxr image classification
Detecting pneumonia, especially coronavirus disease 2019 (COVID-19), from chest X-ray
(CXR) images is one of the most effective ways for disease diagnosis and patient triage. The …
(CXR) images is one of the most effective ways for disease diagnosis and patient triage. The …
Content Delivery Models for Distributed and Cooperative Media Algorithms in Mobile Networks
DD Rao, D Dhabliya, A Dhore… - 2024 15th …, 2024 - ieeexplore.ieee.org
Content transport fashions for allotted and Cooperative Media Algorithms in cellular
Networks (DC-MAMR) is a unique technique to providing multimedia content material in …
Networks (DC-MAMR) is a unique technique to providing multimedia content material in …