ISLES 2015-A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI
Ischemic stroke is the most common cerebrovascular disease, and its diagnosis, treatment,
and study relies on non-invasive imaging. Algorithms for stroke lesion segmentation from …
and study relies on non-invasive imaging. Algorithms for stroke lesion segmentation from …
Computational approaches for acute traumatic brain injury image recognition
E Lin, EL Yuh - Frontiers in neurology, 2022 - frontiersin.org
In recent years, there have been major advances in deep learning algorithms for image
recognition in traumatic brain injury (TBI). Interest in this area has increased due to the …
recognition in traumatic brain injury (TBI). Interest in this area has increased due to the …
Automated segmentation and classification of brain stroke using expectation-maximization and random forest classifier
Magnetic resonance imaging (MRI) is effectively used for accurate diagnosis of acute
ischemic stroke. This paper presents an automated method based on computer aided …
ischemic stroke. This paper presents an automated method based on computer aided …
[HTML][HTML] White matter hyperintensity and stroke lesion segmentation and differentiation using convolutional neural networks
White matter hyperintensities (WMH) are a feature of sporadic small vessel disease also
frequently observed in magnetic resonance images (MRI) of healthy elderly subjects. The …
frequently observed in magnetic resonance images (MRI) of healthy elderly subjects. The …
Application of machine learning techniques for characterization of ischemic stroke with MRI images: a review
Magnetic resonance imaging (MRI) is a standard tool for the diagnosis of stroke, but its
manual interpretation by experts is arduous and time-consuming. Thus, there is a need for …
manual interpretation by experts is arduous and time-consuming. Thus, there is a need for …
Deep learning-based detection and segmentation of diffusion abnormalities in acute ischemic stroke
CF Liu, J Hsu, X Xu, S Ramachandran… - Communications …, 2021 - nature.com
Background Accessible tools to efficiently detect and segment diffusion abnormalities in
acute strokes are highly anticipated by the clinical and research communities. Methods We …
acute strokes are highly anticipated by the clinical and research communities. Methods We …
Automatic ischemic stroke lesion segmentation from computed tomography perfusion images by image synthesis and attention-based deep neural networks
Ischemic stroke lesion segmentation from Computed Tomography Perfusion (CTP) images
is important for accurate diagnosis of stroke in acute care units. However, it is challenged by …
is important for accurate diagnosis of stroke in acute care units. However, it is challenged by …
Classifiers for ischemic stroke lesion segmentation: a comparison study
Motivation Ischemic stroke, triggered by an obstruction in the cerebral blood supply, leads to
infarction of the affected brain tissue. An accurate and reproducible automatic segmentation …
infarction of the affected brain tissue. An accurate and reproducible automatic segmentation …
Extra tree forests for sub-acute ischemic stroke lesion segmentation in MR sequences
Background To analyse the relationship between structure and (dys-) function of the brain
after stroke, accurate and repeatable segmentation of the lesion area in magnetic resonance …
after stroke, accurate and repeatable segmentation of the lesion area in magnetic resonance …
[HTML][HTML] FeMA: Feature matching auto-encoder for predicting ischaemic stroke evolution and treatment outcome
Although, predicting ischaemic stroke evolution and treatment outcome provide important
information one step towards individual treatment planning, classifying functional outcome …
information one step towards individual treatment planning, classifying functional outcome …