Towards Reproducible Results: Validating CT Hemorrhage-Detection Algorithms on Standard Datasets
N Damodaran, R Gowtham - AJNR: American Journal of …, 2018 - ncbi.nlm.nih.gov
We read with great interest the work by Chang et al1 entitled,“Hybrid 3D/2D Convolutional
Neural Network for Hemorrhage Evaluation on Head CT.” Using a custom hybrid 3D/2D …
Neural Network for Hemorrhage Evaluation on Head CT.” Using a custom hybrid 3D/2D …
Hybrid 3D/2D convolutional neural network for hemorrhage evaluation on head CT
PD Chang, E Kuoy, J Grinband… - American Journal …, 2018 - Am Soc Neuroradiology
BACKGROUND AND PURPOSE: Convolutional neural networks are a powerful technology
for image recognition. This study evaluates a convolutional neural network optimized for the …
for image recognition. This study evaluates a convolutional neural network optimized for the …
Abstract WP68: Interpretable Deep Learning-based Characterization of Intracranial Hemorrhage on Head CT
Background: Machine learning algorithms have proven accurate in the detection of
intracranial hemorrhage (ICH) on head CT. Most reported algorithms, however, are limited to …
intracranial hemorrhage (ICH) on head CT. Most reported algorithms, however, are limited to …
Expert-level detection of acute intracranial hemorrhage on head computed tomography using deep learning
Computed tomography (CT) of the head is used worldwide to diagnose neurologic
emergencies. However, expertise is required to interpret these scans, and even highly …
emergencies. However, expertise is required to interpret these scans, and even highly …
Detecting intracranial hemorrhage with deep learning
Initial results are reported on automated detection of intracranial hemorrhage from CT, which
would be valuable in a computer-aided diagnosis system to help the radiologist detect …
would be valuable in a computer-aided diagnosis system to help the radiologist detect …
Comment on “Deep learning-assisted detection and segmentation of intracranial hemorrhage in noncontrast computed tomography scans of acute stroke patients: a …
W Jiang, Y Tian, Y Shen - International Journal of Surgery, 2024 - journals.lww.com
Dear Editor, Hu et al [1] recently conducted a systematic review and meta-analysis to
evaluate the effectiveness of deep learning algorithms in detecting and segmenting …
evaluate the effectiveness of deep learning algorithms in detecting and segmenting …
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 …
A convolutional neural network for intracranial hemorrhage detection in non-contrast CT
A Patel, R Manniesing - Medical Imaging 2018: Computer …, 2018 - spiedigitallibrary.org
The assessment of the presence of intracranial hemorrhage is a crucial step in the work-up
of patients requiring emergency care. Fast and accurate detection of intracranial …
of patients requiring emergency care. Fast and accurate detection of intracranial …
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 …
Accurate and efficient intracranial hemorrhage detection and subtype classification in 3D CT scans with convolutional and long short-term memory neural networks
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 …
challenge, which is based on the RSNA 2019 Brain CT Hemorrhage dataset. The proposed …
