Automated cerebral hemorrhage detection using RAPID
BACKGROUND AND PURPOSE: Intracranial hemorrhage (ICH) is an important event that is
diagnosed on head NCCT. Increased NCCT utilization in busy hospitals may limit timely …
diagnosed on head NCCT. Increased NCCT utilization in busy hospitals may limit timely …
[HTML][HTML] Deep learning algorithm in detecting intracranial hemorrhages on emergency computed tomographies
A Kundisch, A Hönning, S Mutze, L Kreissl, F Spohn… - PLoS …, 2021 - journals.plos.org
Background Highly accurate detection of intracranial hemorrhages (ICH) on head computed
tomography (HCT) scans can prove challenging at high-volume centers. This study aimed to …
tomography (HCT) scans can prove challenging at high-volume centers. This study aimed to …
[HTML][HTML] A deep learning algorithm for automatic detection and classification of acute intracranial hemorrhages in head CT scans
Acute Intracranial hemorrhage (ICH) is a life-threatening disease that requires emergency
medical attention, which is routinely diagnosed using non-contrast head CT imaging. The …
medical attention, which is routinely diagnosed using non-contrast head CT imaging. The …
Assessment of an artificial intelligence algorithm for detection of intracranial hemorrhage
RA Rava, SE Seymour, ME LaQue, BA Peterson… - World Neurosurgery, 2021 - Elsevier
Background Immediate and accurate detection of intracranial hemorrhages (ICHs) is
essential to provide a good clinical outcome for patients with ICH. Artificial intelligence has …
essential to provide a good clinical outcome for patients with ICH. Artificial intelligence has …
[HTML][HTML] Performance testing of a novel deep learning algorithm for the detection of intracranial hemorrhage and first trial under clinical conditions
P Gruschwitz, JP Grunz, PJ Kuhl, A Kosmala… - Neuroscience …, 2021 - Elsevier
Purpose We evaluate the performance of a deep learning-based pipeline using a Dense U-
net architecture for detection of intracranial hemorrhage (ICH) in unenhanced head …
net architecture for detection of intracranial hemorrhage (ICH) in unenhanced head …
Analysis of head CT scans flagged by deep learning software for acute intracranial hemorrhage
DT Ginat - Neuroradiology, 2020 - Springer
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 …
worklist prioritization of acute intracranial hemorrhage on non-contrast head CT (NCCT) in …
Artificial intelligence with statistical confidence scores for detection of acute or subacute hemorrhage on noncontrast CT head scans
Purpose To present a method that automatically detects, subtypes, and locates acute or
subacute intracranial hemorrhage (ICH) on noncontrast CT (NCCT) head scans; generates …
subacute intracranial hemorrhage (ICH) on noncontrast CT (NCCT) head scans; generates …
[HTML][HTML] Efficiency of a deep learning-based artificial intelligence diagnostic system in spontaneous intracerebral hemorrhage volume measurement
T Wang, N Song, L Liu, Z Zhu, B Chen, W Yang… - BMC Medical …, 2021 - Springer
Background Accurate measurement of hemorrhage volume is critical for both the prediction
of prognosis and the selection of appropriate clinical treatment after spontaneous …
of prognosis and the selection of appropriate clinical treatment after spontaneous …
[HTML][HTML] Precise diagnosis of intracranial hemorrhage and subtypes using a three-dimensional joint convolutional and recurrent neural network
Objectives To evaluate the performance of a novel three-dimensional (3D) joint
convolutional and recurrent neural network (CNN-RNN) for the detection of intracranial …
convolutional and recurrent neural network (CNN-RNN) for the detection of intracranial …
[HTML][HTML] Evaluation of techniques to improve a deep learning algorithm for the automatic detection of intracranial haemorrhage on CT head imaging
Background Deep learning (DL) algorithms are playing an increasing role in automatic
medical image analysis. Purpose To evaluate the performance of a DL model for the …
medical image analysis. Purpose To evaluate the performance of a DL model for the …
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