Neuroimaging and deep learning for brain stroke detection-A review of recent advancements and future prospects
Background and objective In recent years, deep learning algorithms have created a massive
impact on addressing research challenges in different domains. The medical field also …
impact on addressing research challenges in different domains. The medical field also …
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 …
[HTML][HTML] PerfU-net: baseline infarct estimation from CT perfusion source data for acute ischemic stroke
L de Vries, BJ Emmer, CBLM Majoie… - Medical image …, 2023 - Elsevier
CT perfusion imaging is commonly used for infarct core quantification in acute ischemic
stroke patients. The outcomes and perfusion maps of CT perfusion software, however, show …
stroke patients. The outcomes and perfusion maps of CT perfusion software, however, show …
MH UNet: A multi-scale hierarchical based architecture for medical image segmentation
UNet and its variations achieve state-of-the-art performances in medical image
segmentation. In end-to-end learning, the training with high-resolution medical images …
segmentation. In end-to-end learning, the training with high-resolution medical images …
Improvement of automatic ischemic stroke lesion segmentation in CT perfusion maps using a learned deep neural network
Acute ischemic stroke is one of the leading causes of death and long-term disability
worldwide. It occurs when a blood clot blocks an artery that supplies blood to the brain …
worldwide. It occurs when a blood clot blocks an artery that supplies blood to the brain …
Ischemic stroke lesion segmentation using mutation model and generative adversarial network
Ischemic stroke lesion segmentation using different types of images, such as Computed
Tomography Perfusion (CTP), is important for medical and Artificial intelligence fields. These …
Tomography Perfusion (CTP), is important for medical and Artificial intelligence fields. These …
[HTML][HTML] A cross-attention-based deep learning approach for predicting functional stroke outcomes using 4D CTP imaging and clinical metadata
Acute ischemic stroke (AIS) remains a global health challenge, leading to long-term
functional disabilities without timely intervention. Spatio-temporal (4D) Computed …
functional disabilities without timely intervention. Spatio-temporal (4D) Computed …
Theoretical analysis and experimental validation of volume bias of soft dice optimized segmentation maps in the context of inherent uncertainty
The clinical interest is often to measure the volume of a structure, which is typically derived
from a segmentation. In order to evaluate and compare segmentation methods, the similarity …
from a segmentation. In order to evaluate and compare segmentation methods, the similarity …
[HTML][HTML] AIFNet: Automatic vascular function estimation for perfusion analysis using deep learning
Perfusion imaging is crucial in acute ischemic stroke for quantifying the salvageable
penumbra and irreversibly damaged core lesions. As such, it helps clinicians to decide on …
penumbra and irreversibly damaged core lesions. As such, it helps clinicians to decide on …
LSTM network for prediction of hemorrhagic transformation in acute stroke
Hemorrhagic transformation (HT) is one of the most devastating complications of reperfusion
therapy in acute ischemic stroke. Prediction of an upcoming HT remains beyond current …
therapy in acute ischemic stroke. Prediction of an upcoming HT remains beyond current …