AIMC Topic: Intracranial Hemorrhages

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Improving Automated Hemorrhage Detection at Sparse-View CT via U-Net-based Artifact Reduction.

Radiology. Artificial intelligence Jul 1, 2024
Purpose To explore the potential benefits of deep learning-based artifact reduction in sparse-view cranial CT scans and its impact on automated hemorrhage detection. Materials and Methods In this retrospective study, a U-Net was trained for artifact ...
Female Male Retrospective Studies Tomography, X-Ray Computed Artifacts Intracranial Hemorrhages Deep Learning Radiographic Image Interpretation, Computer-Assisted Humans
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Semi-supervised Learning for Generalizable Intracranial Hemorrhage Detection and Segmentation.

Radiology. Artificial intelligence May 1, 2024
Purpose To develop and evaluate a semi-supervised learning model for intracranial hemorrhage detection and segmentation on an out-of-distribution head CT evaluation set. Materials and Methods This retrospective study used semi-supervised learning to ...
Machine Learning Retrospective Studies Humans Benchmarking Intracranial Hemorrhages Supervised Machine Learning
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Examination-Level Supervision for Deep Learning-based Intracranial Hemorrhage Detection on Head CT Scans.

Radiology. Artificial intelligence Jan 1, 2024
Purpose To compare the effectiveness of weak supervision (ie, with examination-level labels only) and strong supervision (ie, with image-level labels) in training deep learning models for detection of intracranial hemorrhage (ICH) on head CT scans. M...
Humans Tomography, X-Ray Computed Deep Learning Prospective Studies Retrospective Studies Intracranial Hemorrhages
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Artificial intelligence for detection of intracranial haemorrhage on head computed tomography scans: diagnostic accuracy in Hong Kong.

Hong Kong medical journal = Xianggang yi xue za zhi Apr 1, 2023
INTRODUCTION: The use of artificial intelligence (AI) to identify acute intracranial haemorrhage (ICH) on computed tomography (CT) scans may facilitate initial imaging interpretation in the accident and emergency department. However, AI model constru...
Intracranial Hemorrhages Tomography, X-Ray Computed Hong Kong Humans Artificial Intelligence Retrospective Studies
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Machine learning technologies in CT-based diagnostics and classification of intracranial hemorrhages.

Zhurnal voprosy neirokhirurgii imeni N. N. Burdenko Jan 1, 2023
This review discusses pooled experience of creation, implementation and effectiveness of machine learning technologies in CT-based diagnosis of intracranial hemorrhages. The authors analyzed 21 original articles between 2015 and 2022 using the follow...
Intracranial Hemorrhages Algorithms Tomography, X-Ray Computed Artificial Intelligence Machine Learning Humans
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Deep Learning-Based Brain Hemorrhage Detection in CT Reports.

Studies in health technology and informatics May 25, 2022
Radiology reports can potentially be used to detect critical cases that need immediate attention from physicians. We focus on detecting Brain Hemorrhage from Computed Tomography (CT) reports. We train a deep learning classifier and observe the effect...
Natural Language Processing Intracranial Hemorrhages Research Report Tomography, X-Ray Computed Humans Deep Learning
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Mass Deployment of Deep Neural Network: Real-Time Proof of Concept With Screening of Intracranial Hemorrhage Using an Open Data Set.

Neurosurgery Apr 1, 2022
BACKGROUND: Intracranial hemorrhage (ICH) is considered an emergency that requires rapid medical or surgical management. Previous studies have used artificial intelligence to attempt to expedite the diagnosis of this pathology on neuroimaging. Howeve...
Intracranial Hemorrhages Humans Neural Networks, Computer Tomography, X-Ray Computed Neuroimaging Artificial Intelligence Retrospective Studies
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Transfer Learning of the ResNet-18 and DenseNet-121 Model Used to Diagnose Intracranial Hemorrhage in CT Scanning.

Current pharmaceutical design Jan 1, 2022
OBJECTIVE: The aim of the study was to verify the ability of the deep learning model to identify five subtypes and normal images in non-contrast enhancement CT of intracranial hemorrhage.
Deep Learning Intracranial Hemorrhages Tomography, X-Ray Computed Sensitivity and Specificity Humans
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Clinical usefulness of deep learning-based automated segmentation in intracranial hemorrhage.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2021
BACKGROUND: Doctors with various specializations and experience order brain computed tomography (CT) to rule out intracranial hemorrhage (ICH). Advanced artificial intelligence (AI) can discriminate subtypes of ICH with high accuracy.
Child Algorithms Humans Neuroimaging Artificial Intelligence Intracranial Hemorrhages Deep Learning
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A Simplified Framework for the Detection of Intracranial Hemorrhage in CT Brain Images Using Deep Learning.

Current medical imaging Jan 1, 2021
BACKGROUND: The need for accurate and timely detection of Intracranial hemorrhage (ICH) is of utmost importance to avoid untoward incidents that may even lead to death. Hence, this presented work leverages the ability of a pretrained deep convolution...
Tomography, X-Ray Computed Intracranial Hemorrhages Deep Learning Humans Neural Networks, Computer Brain
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