The prediction of brain cancer occurrence and risk assessment of brain hemorrhage using a hybrid deep learning (DL) technique is a critical area of research in medical imaging analysis. One prominent challenge in this field is the accurate identifica...
BACKGROUND: Symptomatic intracranial hemorrhage (sICH) after mechanical thrombectomy (MT) is associated with worse outcomes. We sought to develop and internally validate a machine learning (ML) model to predict sICH prior to MT in patients with anter...
BACKGROUND: Intracranial hemorrhages (ICH) are life-threatening conditions that require rapid detection and precise subtype classification. Automated segmentation and volumetric analysis using deep learning can enhance clinical decision-making.
Non-enhanced head computed tomography is widely used for patients presenting with head trauma or stroke, given acute intracranial hemorrhage significantly influences clinical decision-making. This study aimed to develop a deep learning algorithm, ref...
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...
BACKGROUND: In clinical settings, intracranial hemorrhages (ICH) are routinely diagnosed using non-contrast CT (NCCT) in emergency stroke imaging for severity assessment. However, compared to magnetic resonance imaging (MRI), ICH shows low contrast a...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
39921928
In recent years, with the increasing attention from researchers towards medical imaging, deep learning-based image segmentation techniques have become mainstream in the field, requiring large amounts of manually annotated data. Annotating datasets fo...
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...
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...