A systematic review on intracranial aneurysm and hemorrhage detection using machine learning and deep learning techniques
SN Ahmed, P Prakasam - Progress in Biophysics and Molecular Biology, 2023 - Elsevier
The risk of discovering an intracranial aneurysm during the initial screening and follow-up
screening are reported as around 11%, and 7% respectively (Zuurbie et al., 2023) to these …
screening are reported as around 11%, and 7% respectively (Zuurbie et al., 2023) to these …
Remaining useful life assessment for lithium-ion batteries using CNN-LSTM-DNN hybrid method
The prediction of a Lithium-ion battery's lifetime is very important for ensuring safety and
reliability. In addition, it is utilized as an early warning system to prevent the battery's failure …
reliability. In addition, it is utilized as an early warning system to prevent the battery's failure …
[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 …
Intracranial hemorrhage detection in head CT using double-branch convolutional neural network, support vector machine, and random forest
Brain hemorrhage is a severe threat to human life, and its timely and correct diagnosis and
treatment are of great importance. Multiple types of brain hemorrhage are distinguished …
treatment are of great importance. Multiple types of brain hemorrhage are distinguished …
An optimal deep learning framework for multi-type hemorrhagic lesions detection and quantification in head CT images for traumatic brain injury
Abstract Traumatic Brain Injury (TBI) could lead to intracranial hemorrhage (ICH), which has
now been identified as a major cause of death after trauma if it is not adequately diagnosed …
now been identified as a major cause of death after trauma if it is not adequately diagnosed …
Intracranial hemorrhage detection using parallel deep convolutional models and boosting mechanism
Intracranial hemorrhage (ICH) can lead to death or disability, which requires immediate
action from radiologists. Due to the heavy workload, less experienced staff, and the …
action from radiologists. Due to the heavy workload, less experienced staff, and the …
Evaluation of transfer learning in deep convolutional neural network models for cardiac short axis slice classification
In computer-aided analysis of cardiac MRI data, segmentations of the left ventricle (LV) and
myocardium are performed to quantify LV ejection fraction and LV mass, and they are …
myocardium are performed to quantify LV ejection fraction and LV mass, and they are …
[HTML][HTML] Deep Gaussian processes for multiple instance learning: Application to CT intracranial hemorrhage detection
Background and objective: Intracranial hemorrhage (ICH) is a life-threatening emergency
that can lead to brain damage or death, with high rates of mortality and morbidity. The fast …
that can lead to brain damage or death, with high rates of mortality and morbidity. The fast …
Images in space and time: real big data in healthcare
E Badr - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
Medical imaging diagnosis is mostly subjective, as it depends on medical experts. Hence,
the service provided is limited by expert opinion variations and image complexity as well …
the service provided is limited by expert opinion variations and image complexity as well …
Improved performance and robustness of multi-task representation learning with consistency loss between pretexts for intracranial hemorrhage identification in head …
With the recent development of deep learning, the classification and segmentation tasks of
computer-aided diagnosis (CAD) using non-contrast head computed tomography (NCCT) …
computer-aided diagnosis (CAD) using non-contrast head computed tomography (NCCT) …