A survey on incorporating domain knowledge into deep learning for medical image analysis
Although deep learning models like CNNs have achieved great success in medical image
analysis, the small size of medical datasets remains a major bottleneck in this area. To …
analysis, the small size of medical datasets remains a major bottleneck in this area. To …
Artificial intelligence to diagnose ischemic stroke and identify large vessel occlusions: a systematic review
NM Murray, M Unberath, GD Hager… - Journal of …, 2020 - jnis.bmj.com
Background and purpose Acute stroke caused by large vessel occlusions (LVOs) requires
emergent detection and treatment by endovascular thrombectomy. However, radiologic LVO …
emergent detection and treatment by endovascular thrombectomy. However, radiologic LVO …
Attention to lesion: Lesion-aware convolutional neural network for retinal optical coherence tomography image classification
Automatic and accurate classification of retinal optical coherence tomography (OCT) images
is essential to assist ophthalmologist in the diagnosis and grading of macular diseases …
is essential to assist ophthalmologist in the diagnosis and grading of macular diseases …
Machine learning for detecting early infarction in acute stroke with non–contrast-enhanced CT
Background Identifying the presence and extent of infarcted brain tissue at baseline plays a
crucial role in the treatment of patients with acute ischemic stroke (AIS). Patients with …
crucial role in the treatment of patients with acute ischemic stroke (AIS). Patients with …
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 …
3D convolutional neural networks applied to CT angiography in the detection of acute ischemic stroke
O Öman, T Mäkelä, E Salli, S Savolainen… - European radiology …, 2019 - Springer
Background The aim of this study was to investigate the feasibility of ischemic stroke
detection from computed tomography angiography source images (CTA-SI) using three …
detection from computed tomography angiography source images (CTA-SI) using three …
EIS-Net: Segmenting early infarct and scoring ASPECTS simultaneously on non-contrast CT of patients with acute ischemic stroke
Detecting early infarct (EI) plays an essential role in patient selection for reperfusion therapy
in the management of acute ischemic stroke (AIS). EI volume at acute or hyper-acute stage …
in the management of acute ischemic stroke (AIS). EI volume at acute or hyper-acute stage …
CLAHE-CapsNet: Efficient retina optical coherence tomography classification using capsule networks with contrast limited adaptive histogram equalization
Manual detection of eye diseases using retina Optical Coherence Tomography (OCT)
images by Ophthalmologists is time consuming, prone to errors and tedious. Previous …
images by Ophthalmologists is time consuming, prone to errors and tedious. Previous …
Investigating the use of a two-stage attention-aware convolutional neural network for the automated diagnosis of otitis media from tympanic membrane images: a …
Y Cai, JG Yu, Y Chen, C Liu, L Xiao, EM Grais… - BMJ open, 2021 - bmjopen.bmj.com
Objectives This study investigated the usefulness and performance of a two-stage attention-
aware convolutional neural network (CNN) for the automated diagnosis of otitis media from …
aware convolutional neural network (CNN) for the automated diagnosis of otitis media from …