Accuracy of artificial intelligence for the detection of intracranial hemorrhage and chronic cerebral microbleeds: A systematic review and pooled analysis
Background Artificial intelligence (AI)-driven software has been developed and become
commercially available within the past few years for the detection of intracranial hemorrhage …
commercially available within the past few years for the detection of intracranial hemorrhage …
A systematic review on intracranial aneurysm and hemorrhage detection using machine learning and deep learning techniques
SN Ahmed, P Prakasam - Progress in Biophysics and Molecular Biology, 2023 - Elsevier
The risk of discovering an intracranial aneurysm during the initial screening and follow-up
screening are reported as around 11%, and 7% respectively (Zuurbie et al., 2023) to these …
screening are reported as around 11%, and 7% respectively (Zuurbie et al., 2023) to these …
Deep learning for hemorrhagic lesion detection and segmentation on brain CT images
L Li, M Wei, BO Liu, K Atchaneeyasakul… - IEEE journal of …, 2020 - ieeexplore.ieee.org
Stroke is an acute cerebral vascular disease that is likely to cause long-term disabilities and
death. Immediate emergency care with accurate diagnosis of computed tomographic (CT) …
death. Immediate emergency care with accurate diagnosis of computed tomographic (CT) …
[HTML][HTML] A deep learning algorithm for automatic detection and classification of acute intracranial hemorrhages in head CT scans
Acute Intracranial hemorrhage (ICH) is a life-threatening disease that requires emergency
medical attention, which is routinely diagnosed using non-contrast head CT imaging. The …
medical attention, which is routinely diagnosed using non-contrast head CT imaging. The …
[HTML][HTML] Accurate and efficient intracranial hemorrhage detection and subtype classification in 3D CT scans with convolutional and long short-term memory neural …
In this paper, we present our system for the RSNA Intracranial Hemorrhage Detection
challenge, which is based on the RSNA 2019 Brain CT Hemorrhage dataset. The proposed …
challenge, which is based on the RSNA 2019 Brain CT Hemorrhage dataset. The proposed …
Synergic deep learning model–based automated detection and classification of brain intracranial hemorrhage images in wearable networks
With an intention of improving healthcare performance, wearable technology products utilize
several digital health sensors which are classically linked into sensor networks, including …
several digital health sensors which are classically linked into sensor networks, including …
An optimal segmentation with deep learning based inception network model for intracranial hemorrhage diagnosis
RF Mansour, NO Aljehane - Neural Computing and Applications, 2021 - Springer
Abstract Traumatic Brain Injury (TBI) leads to intracranial hemorrhages (ICH), which is a
severe illness resulted in death if it is not properly diagnosed and treated in the earlier stage …
severe illness resulted in death if it is not properly diagnosed and treated in the earlier stage …
Artificial intelligence with big data analytics-based brain intracranial hemorrhage e-diagnosis using CT images
RF Mansour, J Escorcia-Gutierrez, M Gamarra… - Neural Computing and …, 2023 - Springer
Due to the fast development of medical imaging technologies, medical image analysis has
entered the period of big data for proper disease diagnosis. At the same time, intracerebral …
entered the period of big data for proper disease diagnosis. At the same time, intracerebral …
[HTML][HTML] Automatic hemorrhage segmentation on head CT scan for traumatic brain injury using 3D deep learning model
The most common cause of long-term disability and death in young adults is a traumatic
brain injury. The decision for surgical intervention for craniotomy is dependent on the injury …
brain injury. The decision for surgical intervention for craniotomy is dependent on the injury …
[HTML][HTML] A fast and fully-automated deep-learning approach for accurate hemorrhage segmentation and volume quantification in non-contrast whole-head CT
This project aimed to develop and evaluate a fast and fully-automated deep-learning
method applying convolutional neural networks with deep supervision (CNN-DS) for …
method applying convolutional neural networks with deep supervision (CNN-DS) for …