Machine learning in action: stroke diagnosis and outcome prediction
The application of machine learning has rapidly evolved in medicine over the past decade.
In stroke, commercially available machine learning algorithms have already been …
In stroke, commercially available machine learning algorithms have already been …
Comparison of vision transformers and convolutional neural networks in medical image analysis: a systematic review
S Takahashi, Y Sakaguchi, N Kouno… - Journal of Medical …, 2024 - Springer
In the rapidly evolving field of medical image analysis utilizing artificial intelligence (AI), the
selection of appropriate computational models is critical for accurate diagnosis and patient …
selection of appropriate computational models is critical for accurate diagnosis and patient …
Edge U-Net: Brain tumor segmentation using MRI based on deep U-Net model with boundary information
Blood clots in the brain are frequently caused by brain tumors. Early detection of these clots
has the potential to significantly lower morbidity and mortality in cases of brain cancer. It is …
has the potential to significantly lower morbidity and mortality in cases of brain cancer. It is …
[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 …
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 …
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 …
[HTML][HTML] Hemorrhagic stroke lesion segmentation using a 3D U-Net with squeeze-and-excitation blocks
Hemorrhagic stroke is the condition involving the rupture of a vessel inside the brain and is
characterized by high mortality rates. Even if the patient survives, stroke can cause …
characterized by high mortality rates. Even if the patient survives, stroke can cause …
Deep learning applications for acute stroke management
IR Chavva, AL Crawford, MH Mazurek… - Annals of …, 2022 - Wiley Online Library
Brain imaging is essential to the clinical care of patients with stroke, a leading cause of
disability and death worldwide. Whereas advanced neuroimaging techniques offer …
disability and death worldwide. Whereas advanced neuroimaging techniques offer …
Multi-method diagnosis of CT images for rapid detection of intracranial hemorrhages based on deep and hybrid learning
Intracranial hemorrhaging is considered a type of disease that affects the brain and is very
dangerous, with high-mortality cases if there is no rapid diagnosis and prompt treatment. CT …
dangerous, with high-mortality cases if there is no rapid diagnosis and prompt treatment. CT …
Automated detection and screening of traumatic brain injury (TBI) using computed tomography images: a comprehensive review and future perspectives
Traumatic brain injury (TBI) occurs due to the disruption in the normal functioning of the
brain by sudden external forces. The primary and secondary injuries due to TBI include …
brain by sudden external forces. The primary and secondary injuries due to TBI include …