[HTML][HTML] A systematic review of deep learning data augmentation in medical imaging: Recent advances and future research directions
Data augmentation involves artificially expanding a dataset by applying various
transformations to the existing data. Recent developments in deep learning have advanced …
transformations to the existing data. Recent developments in deep learning have advanced …
An analysis of deep transfer learning-based approaches for prediction and prognosis of multiple respiratory diseases using pulmonary images
Respiratory diseases can lead to lung failure, which happens when the lungs cannot give
the body enough oxygen. These diseases can be diagnosed using medical data, lung …
the body enough oxygen. These diseases can be diagnosed using medical data, lung …
Prospective evaluation of AI triage of pulmonary emboli on CT pulmonary angiograms
Background Artificial intelligence (AI) algorithms have shown high accuracy for detection of
pulmonary embolism (PE) on CT pulmonary angiography (CTPA) studies in academic …
pulmonary embolism (PE) on CT pulmonary angiography (CTPA) studies in academic …
Scunet++: Swin-unet and cnn bottleneck hybrid architecture with multi-fusion dense skip connection for pulmonary embolism ct image segmentation
Pulmonary embolism (PE) is a prevalent lung disease that can lead to right ventricular
hypertrophy and failure in severe cases, ranking second in severity only to myocardial …
hypertrophy and failure in severe cases, ranking second in severity only to myocardial …
Automated detection and segmentation of pulmonary embolisms on computed tomography pulmonary angiography (CTPA) using deep learning but without manual …
We present a novel computer algorithm to automatically detect and segment pulmonary
embolisms (PEs) on computed tomography pulmonary angiography (CTPA). This algorithm …
embolisms (PEs) on computed tomography pulmonary angiography (CTPA). This algorithm …
INSPECT: a multimodal dataset for patient outcome prediction of pulmonary embolisms
Synthesizing information from various data sources plays a crucial role in the practice of
modern medicine. Current applications of artificial intelligence in medicine often focus on …
modern medicine. Current applications of artificial intelligence in medicine often focus on …
[HTML][HTML] Modern imaging of acute pulmonary embolism
CMM de Jong, LJM Kroft, TE van Mens, MV Huisman… - Thrombosis research, 2024 - Elsevier
The first-choice imaging test for visualization of thromboemboli in the pulmonary vasculature
in patients with suspected acute pulmonary embolism (PE) is multidetector computed …
in patients with suspected acute pulmonary embolism (PE) is multidetector computed …
Dual-layer dual-energy CT-derived pulmonary perfusion for the differentiation of acute pulmonary embolism and chronic thromboembolic pulmonary hypertension
Objectives To evaluate dual-layer dual-energy computed tomography (dlDECT)–derived
pulmonary perfusion maps for differentiation between acute pulmonary embolism (PE) and …
pulmonary perfusion maps for differentiation between acute pulmonary embolism (PE) and …
[HTML][HTML] Deep learning in computed tomography pulmonary angiography imaging: A dual-pronged approach for pulmonary embolism detection
The increasing reliance on Computed Tomography Pulmonary Angiography (CTPA) for
Pulmonary Embolism (PE) diagnosis presents challenges and a pressing need for improved …
Pulmonary Embolism (PE) diagnosis presents challenges and a pressing need for improved …
A deep learning approach for automated diagnosis of pulmonary embolism on computed tomographic pulmonary angiography
Background Computed tomographic pulmonary angiography (CTPA) is the diagnostic
standard for confirming pulmonary embolism (PE). Since PE is a life-threatening condition …
standard for confirming pulmonary embolism (PE). Since PE is a life-threatening condition …