Review of deep learning approaches for the segmentation of multiple sclerosis lesions on brain MRI
In recent years, there have been multiple works of literature reviewing methods for
automatically segmenting multiple sclerosis (MS) lesions. However, there is no literature …
automatically segmenting multiple sclerosis (MS) lesions. However, there is no literature …
Commercial volumetric MRI reporting tools in multiple sclerosis: a systematic review of the evidence
Z Mendelsohn, HG Pemberton, J Gray, O Goodkin… - Neuroradiology, 2023 - Springer
Purpose MRI is integral to the diagnosis of multiple sclerosis (MS) and is important for
clinical prognostication. Quantitative volumetric reporting tools (QReports) can improve the …
clinical prognostication. Quantitative volumetric reporting tools (QReports) can improve the …
A hybrid fuzzy brain-storm optimization algorithm for the classification of brain tumor MRI images
C Narmatha, SM Eljack, AARM Tuka… - Journal of ambient …, 2020 - Springer
Brain tumor is the most severe nervous system disorder and causes significant damage to
health and leads to death. Glioma was a primary intracranial tumor with the most elevated …
health and leads to death. Glioma was a primary intracranial tumor with the most elevated …
Intrusion detection in networks using crow search optimization algorithm with adaptive neuro-fuzzy inference system
Intrusion detection system has become the fundamental part for the network security and
essential for network security because of the expansion of attacks which causes many …
essential for network security because of the expansion of attacks which causes many …
BIANCA‐MS: An optimized tool for automated multiple sclerosis lesion segmentation
In this work we present BIANCA‐MS, a novel tool for brain white matter lesion segmentation
in multiple sclerosis (MS), able to generalize across both the wide spectrum of MRI …
in multiple sclerosis (MS), able to generalize across both the wide spectrum of MRI …
FFUNet: A novel feature fusion makes strong decoder for medical image segmentation
J Xie, R Zhu, Z Wu, J Ouyang - IET signal processing, 2022 - Wiley Online Library
Convolutional neural networks (CNNs) have strong ability to extract local features, but it is
slightly lacking in extracting global contexts. In contrast, transformers are good at long …
slightly lacking in extracting global contexts. In contrast, transformers are good at long …
A survey of deep learning methods for multiple sclerosis identification using brain MRI images
M Sah, C Direkoglu - Neural Computing and Applications, 2022 - Springer
Multiple sclerosis (MS) is one of the most common inflammatory neurological diseases in
young adults. There are three types of MS:(1) In relapsing remitting MS (RRMS), people …
young adults. There are three types of MS:(1) In relapsing remitting MS (RRMS), people …
Certain Investigations on IoT system for COVID-19
S Jaafari, A Alhasani, SM Almutairi - … Conference on Computing …, 2020 - ieeexplore.ieee.org
Corona Viruses are a group of viruses that can cause diseases such as colds, severe acute
respiratory syndrome (SARS) and the Middle East Respiratory Syndrome (MERS). A new …
respiratory syndrome (SARS) and the Middle East Respiratory Syndrome (MERS). A new …
Automotive domain controller
D Wang, S Ganesan - 2020 International Conference on …, 2020 - ieeexplore.ieee.org
Today, every electronic control system in the car, such as Instrument Cluster, Infotainment,
Anti-lock braking system, Engine Management System, Transmission Control Unit, and Body …
Anti-lock braking system, Engine Management System, Transmission Control Unit, and Body …
IoT based empowerment by smart health monitoring, smart education and smart jobs
S Eeshwaroju, P Jakkula… - … conference on computing …, 2020 - ieeexplore.ieee.org
This paper describes the idea and overview of enhancing the empowerment using internet
of Things (IoT) via three main pillars of the society ie, health, education and wealth …
of Things (IoT) via three main pillars of the society ie, health, education and wealth …