AIMC Topic: Intracranial Hemorrhages

Clear Filters Showing 71 to 80 of 94 articles

Hybrid 3D/2D Convolutional Neural Network for Hemorrhage Evaluation on Head CT.

AJNR. American journal of neuroradiology Jul 26, 2018
BACKGROUND AND PURPOSE: Convolutional neural networks are a powerful technology for image recognition. This study evaluates a convolutional neural network optimized for the detection and quantification of intraparenchymal, epidural/subdural, and suba...
Intracranial Hemorrhages Sensitivity and Specificity Deep Learning Imaging, Three-Dimensional Neuroimaging Humans Prospective Studies Tomography, X-Ray Computed
View on PubMed DOI

Intelligent Word Embeddings of Free-Text Radiology Reports.

AMIA ... Annual Symposium proceedings. AMIA Symposium Apr 16, 2018
Radiology reports are a rich resource for advancing deep learning applications in medicine by leveraging the large volume of data continuously being updated, integrated, and shared. However, there are significant challenges as well, largely due to th...
Machine Learning Electronic Health Records Natural Language Processing Humans Intracranial Hemorrhages Datasets as Topic Semantics Radiology Information Systems
View on PubMed

Introducing the Big Knowledge to Use (BK2U) challenge.

Annals of the New York Academy of Sciences Oct 17, 2016
The purpose of the Big Data to Knowledge initiative is to develop methods for discovering new knowledge from large amounts of data. However, if the resulting knowledge is so large that it resists comprehension, referred to here as Big Knowledge (BK),...
Humans Intracranial Hemorrhages Animals Decision Making, Computer-Assisted Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Systematized Nomenclature of Medicine Terminology as Topic Drug Interactions Computational Biology Knowledge Bases Translational Research, Biomedical Models, Neurological Data Mining Pharmaceutical Preparations
View on PubMed DOI

Outcomes and Complications After Endovascular Treatment of Brain Arteriovenous Malformations: A Prognostication Attempt Using Artificial Intelligence.

World neurosurgery Sep 28, 2016
PURPOSE: To identify factors influencing outcome in brain arteriovenous malformations (BAVM) treated with endovascular embolization. We also assessed the feasibility of using machine learning techniques to prognosticate and predict outcome and compar...
Endovascular Procedures Cerebral Angiography Intracranial Arteriovenous Malformations Male Middle Aged Female Postoperative Complications Young Adult Humans Outcome Assessment, Health Care Adult Artificial Intelligence Intracranial Hemorrhages Treatment Outcome Retrospective Studies Follow-Up Studies
View on PubMed DOI

MEF-Net: Multi-scale and edge feature fusion network for intracranial hemorrhage segmentation in CT images.

Computers in biology and medicine Jun 1, 2025
Intracranial Hemorrhage (ICH) refers to cerebral bleeding resulting from ruptured blood vessels within the brain. Delayed and inaccurate diagnosis and treatment of ICH can lead to fatality or disability. Therefore, early and precise diagnosis of intr...
Tomography, X-Ray Computed Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Intracranial Hemorrhages Humans Neural Networks, Computer Algorithms
View on PubMed DOI

Intracranial hemorrhage segmentation and classification framework in computer tomography images using deep learning techniques.

Scientific reports May 17, 2025
By helping the neurosurgeon create treatment strategies that increase the survival rate, automotive diagnosis and CT (Computed Tomography) hemorrhage segmentation (CT) could be beneficial. Owing to the significance of medical image segmentation and t...
Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Intracranial Hemorrhages Humans
View on PubMed DOI

Applying Conformal Prediction to a Deep Learning Model for Intracranial Hemorrhage Detection to Improve Trustworthiness.

Radiology. Artificial intelligence Mar 1, 2025
Purpose To apply conformal prediction to a deep learning (DL) model for intracranial hemorrhage (ICH) detection and evaluate model performance in detection as well as model accuracy in identifying challenging cases. Materials and Methods This was a r...
Radiographic Image Interpretation, Computer-Assisted Intracranial Hemorrhages Retrospective Studies Tomography, X-Ray Computed Female Middle Aged Humans Deep Learning Adult Male
View on PubMed DOI

Deep-Learning Generated Synthetic Material Decomposition Images Based on Single-Energy CT to Differentiate Intracranial Hemorrhage and Contrast Staining Within 24 Hours After Endovascular Thrombectomy.

CNS neuroscience & therapeutics Jan 1, 2025
AIMS: To develop a transformer-based generative adversarial network (trans-GAN) that can generate synthetic material decomposition images from single-energy CT (SECT) for real-time detection of intracranial hemorrhage (ICH) after endovascular thrombe...
Female Aged Male Middle Aged Humans Retrospective Studies Tomography, X-Ray Computed Endovascular Procedures Deep Learning Thrombectomy Contrast Media Intracranial Hemorrhages
View on PubMed DOI

Precise Image-level Localization of Intracranial Hemorrhage on Head CT Scans with Deep Learning Models Trained on Study-level Labels.

Radiology. Artificial intelligence Nov 1, 2024
Purpose To develop a highly generalizable weakly supervised model to automatically detect and localize image-level intracranial hemorrhage (ICH) by using study-level labels. Materials and Methods In this retrospective study, the proposed model was pr...
Middle Aged Deep Learning Radiographic Image Interpretation, Computer-Assisted Intracranial Hemorrhages Aged, 80 and over Adult Male Humans Female Aged Retrospective Studies Tomography, X-Ray Computed
View on PubMed DOI

Deep Learning to Detect Intracranial Hemorrhage in a National Teleradiology Program and the Impact on Interpretation Time.

Radiology. Artificial intelligence Sep 1, 2024
The diagnostic performance of an artificial intelligence (AI) clinical decision support solution for acute intracranial hemorrhage (ICH) detection was assessed in a large teleradiology practice. The impact on radiologist read times and system efficie...
Intracranial Hemorrhages Teleradiology Deep Learning Time Factors Radiographic Image Interpretation, Computer-Assisted Sensitivity and Specificity Male Middle Aged Humans Retrospective Studies Aged Adult Tomography, X-Ray Computed Female
View on PubMed DOI
Popular Topics
Recent Journals