Multi-task deep learning for medical image computing and analysis: A review
The renaissance of deep learning has provided promising solutions to various tasks. While
conventional deep learning models are constructed for a single specific task, multi-task deep …
conventional deep learning models are constructed for a single specific task, multi-task deep …
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 …
Evaluating nnU-Net for early ischemic change segmentation on non-contrast computed tomography in patients with Acute Ischemic Stroke
H El-Hariri, LASM Neto, P Cimflova, F Bala… - Computers in biology …, 2022 - Elsevier
Identifying the presence and extent of early ischemic changes (EIC) on Non-Contrast
Computed Tomography (NCCT) is key to diagnosing and making time-sensitive treatment …
Computed Tomography (NCCT) is key to diagnosing and making time-sensitive treatment …
APIS: a paired CT-MRI dataset for ischemic stroke segmentation-methods and challenges
Stroke, the second leading cause of mortality globally, predominantly results from ischemic
conditions. Immediate attention and diagnosis, related to the characterization of brain …
conditions. Immediate attention and diagnosis, related to the characterization of brain …
Hybrid CNN-Transformer Network with Circular Feature Interaction for Acute Ischemic Stroke Lesion Segmentation on Non-contrast CT Scans
Lesion segmentation is a fundamental step for the diagnosis of acute ischemic stroke (AIS).
Non-contrast CT (NCCT) is still a mainstream imaging modality for AIS lesion measurement …
Non-contrast CT (NCCT) is still a mainstream imaging modality for AIS lesion measurement …
Improving the diagnosis of acute ischemic stroke on non-contrast CT using deep learning: a multicenter study
W Chen, J Wu, R Wei, S Wu, C Xia, D Wang, D Liu… - Insights into …, 2022 - Springer
Objective This study aimed to develop a deep learning (DL) model to improve the diagnostic
performance of EIC and ASPECTS in acute ischemic stroke (AIS). Methods Acute ischemic …
performance of EIC and ASPECTS in acute ischemic stroke (AIS). Methods Acute ischemic …
Application of deep learning to ischemic and hemorrhagic stroke computed tomography and magnetic resonance imaging
Deep Learning (DL) algorithm holds great potential in the field of stroke imaging. It has been
applied not only to the “downstream” side such as lesion detection, treatment decision …
applied not only to the “downstream” side such as lesion detection, treatment decision …
Deep learning-based automatic ASPECTS calculation can improve diagnosis efficiency in patients with acute ischemic stroke: a multicenter study
J Wei, K Shang, X Wei, Y Zhu, Y Yuan, M Wang… - European …, 2024 - Springer
Abstract Objectives The Alberta Stroke Program Early CT Score (ASPECTS), a systematic
method for assessing ischemic changes in acute ischemic stroke using non-contrast …
method for assessing ischemic changes in acute ischemic stroke using non-contrast …
Asymmetry disentanglement network for interpretable acute ischemic stroke infarct segmentation in non-contrast CT scans
Accurate infarct segmentation in non-contrast CT (NCCT) images is a crucial step toward
computer-aided acute ischemic stroke (AIS) assessment. In clinical practice, bilateral …
computer-aided acute ischemic stroke (AIS) assessment. In clinical practice, bilateral …
Localization of early infarction on non-contrast CT images in acute ischemic stroke with deep learning approach
S Mohapatra, TH Lee, PK Sahoo, CY Wu - Scientific Reports, 2023 - nature.com
Localization of early infarction on first-line Non-contrast computed tomogram (NCCT) guides
prompt treatment to improve stroke outcome. Our previous study has shown a good …
prompt treatment to improve stroke outcome. Our previous study has shown a good …