AIMC Topic: Intracranial Hemorrhages

Clear Filters Showing 61 to 70 of 94 articles

Improvement of the diagnostic accuracy for intracranial haemorrhage using deep learning-based computer-assisted detection.

Neuroradiology Oct 6, 2020
PURPOSE: To elucidate the effect of deep learning-based computer-assisted detection (CAD) on the performance of different-level physicians in detecting intracranial haemorrhage using CT.
Sensitivity and Specificity Diagnosis, Computer-Assisted Deep Learning Retrospective Studies Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Intracranial Hemorrhages Humans Computers
View on PubMed DOI

Accurate and Efficient Intracranial Hemorrhage Detection and Subtype Classification in 3D CT Scans with Convolutional and Long Short-Term Memory Neural Networks.

Sensors (Basel, Switzerland) Oct 1, 2020
In this paper, we present our system for the RSNA Intracranial Hemorrhage Detection challenge, which is based on the RSNA 2019 Brain CT Hemorrhage dataset. The proposed system is based on a lightweight deep neural network architecture composed of a c...
Neural Networks, Computer Tomography, X-Ray Computed Humans Intracranial Hemorrhages
View on PubMed DOI

CT window trainable neural network for improving intracranial hemorrhage detection by combining multiple settings.

Artificial intelligence in medicine May 20, 2020
Window settings to rescale and contrast stretch raw data from radiographic images such as Computed Tomography (CT), X-ray and Magnetic Resonance images is a crucial step as data pre-processing to examine abnormalities and diagnose diseases. We propos...
Neural Networks, Computer Tomography, X-Ray Computed Magnetic Resonance Imaging Humans Intracranial Hemorrhages
View on PubMed DOI

Utility of Artificial Intelligence Tool as a Prospective Radiology Peer Reviewer - Detection of Unreported Intracranial Hemorrhage.

Academic radiology Feb 24, 2020
RATIONALE AND OBJECTIVES: Misdiagnosis of intracranial hemorrhage (ICH) can adversely impact patient outcomes. The increasing workload on the radiologists may increase the chance of error and compromise the quality of care provided by the radiologist...
Humans Artificial Intelligence Radiology Intracranial Hemorrhages Prospective Studies Retrospective Studies
View on PubMed DOI

Analysis of head CT scans flagged by deep learning software for acute intracranial hemorrhage.

Neuroradiology Dec 11, 2019
PURPOSE: To analyze the implementation of deep learning software for the detection and worklist prioritization of acute intracranial hemorrhage on non-contrast head CT (NCCT) in various clinical settings at an academic medical center.
Female Sensitivity and Specificity Male Prospective Studies Tomography, X-Ray Computed Intracranial Hemorrhages Deep Learning Predictive Value of Tests Acute Disease Humans Software
View on PubMed DOI

Expert-level detection of acute intracranial hemorrhage on head computed tomography using deep learning.

Proceedings of the National Academy of Sciences of the United States of America Oct 21, 2019
Computed tomography (CT) of the head is used worldwide to diagnose neurologic emergencies. However, expertise is required to interpret these scans, and even highly trained experts may miss subtle life-threatening findings. For head CT, a unique chall...
Deep Learning Acute Disease Intracranial Hemorrhages Neural Networks, Computer Algorithms Tomography, X-Ray Computed Humans
View on PubMed DOI

Application of Deep Learning in Neuroradiology: Brain Haemorrhage Classification Using Transfer Learning.

Computational intelligence and neuroscience Jun 3, 2019
In this paper, we address the problem of identifying brain haemorrhage which is considered as a tedious task for radiologists, especially in the early stages of the haemorrhage. The problem is solved using a deep learning approach where a convolution...
Hemorrhage Intracranial Hemorrhages Support Vector Machine Radiologists Neural Networks, Computer Humans Machine Learning Deep Learning
View on PubMed DOI

Precise diagnosis of intracranial hemorrhage and subtypes using a three-dimensional joint convolutional and recurrent neural network.

European radiology Apr 30, 2019
OBJECTIVES: To evaluate the performance of a novel three-dimensional (3D) joint convolutional and recurrent neural network (CNN-RNN) for the detection of intracranial hemorrhage (ICH) and its five subtypes (cerebral parenchymal, intraventricular, sub...
Algorithms Intracranial Hemorrhages Retrospective Studies Tomography, X-Ray Computed Female Reproducibility of Results Aged Infant Adult Deep Learning Aged, 80 and over Male Humans Adolescent Young Adult Child, Preschool Middle Aged Child Imaging, Three-Dimensional
View on PubMed DOI

An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasets.

Nature biomedical engineering Dec 17, 2018
Owing to improvements in image recognition via deep learning, machine-learning algorithms could eventually be applied to automated medical diagnoses that can guide clinical decision-making. However, these algorithms remain a 'black box' in terms of h...
Algorithms Acute Disease Deep Learning Databases as Topic Intracranial Hemorrhages
View on PubMed DOI

Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study.

Lancet (London, England) Oct 11, 2018
BACKGROUND: Non-contrast head CT scan is the current standard for initial imaging of patients with head trauma or stroke symptoms. We aimed to develop and validate a set of deep learning algorithms for automated detection of the following key finding...
Skull Fractures Humans Retrospective Studies Datasets as Topic Intracranial Hemorrhages Tomography, X-Ray Computed Algorithms Head Brain Injuries Trauma Severity Indices Deep Learning Triage
View on PubMed DOI
Popular Topics
Recent Journals