AIMC Topic: Cerebral Hemorrhage

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Surgical Robotics for Intracerebral Hemorrhage Treatment: State of the Art and Future Directions.

Annals of biomedical engineering Jul 5, 2023
Intracerebral hemorrhage (ICH) is a stroke subtype with high mortality and disability, and there are no proven medical treatments that can improve the functional outcome of ICH patients. Robot-assisted neurosurgery is a significant advancement in the...
Humans Robotics Minimally Invasive Surgical Procedures Neurosurgical Procedures Treatment Outcome Cerebral Hemorrhage
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A Retrospective Study of Puncture and Drainage for Primary Brainstem Hemorrhage With the Assistance of a Surgical Robot.

The neurologist Mar 1, 2023
BACKGROUND: Whether primary brainstem hemorrhage (PBH) should be treated with a conservative treatment or with surgical intervention (such as craniotomy, puncture, and drainage) is still controversial. The aim of this study was to assess the feasibil...
Cerebral Hemorrhage Brain Stem Drainage Hematoma Robotics Punctures Paracentesis Humans Retrospective Studies
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The Current State of Susceptibility-Weighted Imaging and Quantitative Susceptibility Mapping in Head Trauma.

Neuroimaging clinics of North America Feb 26, 2023
Susceptibility-weighted imaging (SWI) is a MR imaging technique suited to detect structural and microstructural abnormalities in traumatic brain injury (TBI). This review article provide an insight in to the physics principles of SWI and its clinical...
Cerebral Hemorrhage Craniocerebral Trauma Humans Biomarkers Artificial Intelligence Magnetic Resonance Imaging
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DeepSWI: Using Deep Learning to Enhance Susceptibility Contrast on T2*-Weighted MRI.

Journal of magnetic resonance imaging : JMRI Feb 2, 2023
BACKGROUND: Although susceptibility-weighted imaging (SWI) is the gold standard for visualizing cerebral microbleeds (CMBs) in the brain, the required phase data are not always available clinically. Having a postprocessing tool for generating SWI con...
Humans Retrospective Studies Sensitivity and Specificity Male Deep Learning Female Adult Magnetic Resonance Imaging Cerebral Hemorrhage
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Deep-learning measurement of intracerebral haemorrhage with mixed precision training: a coarse-to-fine study.

Clinical radiology Jan 22, 2023
AIM: To develop a unified deep-learning-based method for automated intracerebral haemorrhage (ICH) segmentation on computed tomography (CT) images with different layer thickness parameters.
Cerebral Hemorrhage Head Deep Learning Image Processing, Computer-Assisted Humans Tomography, X-Ray Computed
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A deep learning model for prognosis prediction after intracranial hemorrhage.

Journal of neuroimaging : official journal of the American Society of Neuroimaging Dec 31, 2022
BACKGROUND AND PURPOSE: Intracranial hemorrhage (ICH) is a common life-threatening condition that must be rapidly diagnosed and treated. However, there is still a lack of consensus regarding treatment, driven to some extent by prognostic uncertainty....
Deep Learning Cerebral Hemorrhage Humans ROC Curve Intracranial Hemorrhages Prognosis
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A machine learning approach for predicting perihematomal edema expansion in patients with intracerebral hemorrhage.

European radiology Dec 6, 2022
OBJECTIVES: Preventing the expansion of perihematomal edema (PHE) represents a novel strategy for the improvement of neurological outcomes in intracerebral hemorrhage (ICH) patients. Our goal was to predict early and delayed PHE expansion using a mac...
Brain Edema Hematoma Machine Learning Humans Edema Cerebral Hemorrhage Artificial Intelligence
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Predicting prognosis of primary pontine hemorrhage using CT image and deep learning.

NeuroImage. Clinical Nov 4, 2022
Prognosis of primary pontine hemorrhage (PPH) is important for treatment planning and patient management. However, only few clinical factors were reported to have prognostic value to PPH. Here, we propose a deep learning (DL) model that mines high-di...
Deep Learning Retrospective Studies Humans Hematoma Cerebral Hemorrhage Tomography, X-Ray Computed Prognosis
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Joint modeling strategy for using electronic medical records data to build machine learning models: an example of intracerebral hemorrhage.

BMC medical informatics and decision making Oct 25, 2022
BACKGROUND: Outliers and class imbalance in medical data could affect the accuracy of machine learning models. For physicians who want to apply predictive models, how to use the data at hand to build a model and what model to choose are very thorny p...
Support Vector Machine Reactive Oxygen Species Humans Machine Learning Cerebral Hemorrhage Electronic Health Records
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Symmetry-Aware Deep Learning for Cerebral Ventricle Segmentation With Intra-Ventricular Hemorrhage.

IEEE journal of biomedical and health informatics Oct 4, 2022
Cerebral ventricles are one of the prominent structures in the brain, segmenting which can provide rich information for brain-related disease diagnosis. Unfortunately, cerebral ventricle segmentation in complex clinical cases, such as in the coexiste...
Brain Cerebral Hemorrhage Humans Deep Learning Cerebral Ventricles Image Processing, Computer-Assisted
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