Computed tomographic pulmonary angiography (CTPA) is the gold standard for pulmonary
embolism (PE) diagnosis. However, this diagnosis is susceptible to misdiagnosis. In this …

Transfer learning from natural images to medical images has been established as one of the
most practical paradigms in deep learning for medical image analysis. To fit this paradigm …

Objectives To evaluate the performance of an AI-powered algorithm for the automatic
detection of pulmonary embolism (PE) on chest computed tomography pulmonary …

Background The aim of this study was to develop and evaluate a deep neural network
model in the automated detection of pulmonary embolism (PE) from computed tomography …

Generative adversarial networks (GANs) have ushered in a revolution in image-to-image
translation. The development and proliferation of GANs raises an interesting question: can …

The first-choice imaging test for visualization of thromboemboli in the pulmonary vasculature
in patients with suspected acute pulmonary embolism (PE) is multidetector computed …

Pulmonary Embolism (PE) represents a thrombus (“blood clot”), usually originating from a
lower extremity vein, that travels to the blood vessels in the lung, causing vascular …

The Internet of Medical Things (IoMT) has revolutionized Ambient Assisted Living (AAL) by
interconnecting smart medical devices. These devices generate a large amount of data …

Background Artificial intelligence (AI) algorithms have shown high accuracy for detection of
pulmonary embolism (PE) on CT pulmonary angiography (CTPA) studies in academic …

Transfer learning has gained attention in medical image analysis due to limited annotated
3D medical datasets for training data-driven deep learning models in the real world. Existing …