Computed Tomography Pulmonary

Computed tomography pulmonary angiography (CTPA) is a crucial imaging technique for diagnosing pulmonary embolism (PE), a life-threatening condition. Current research focuses on improving PE detection and risk stratification using CTPA images, employing deep learning models such as convolutional neural networks (CNNs) and generative adversarial networks (GANs). These models are being used to improve diagnostic accuracy, potentially through automated PE detection, prediction of mortality risk, and even generating synthetic CTPA images from less expensive and readily available chest X-rays to improve access to this vital diagnostic tool. This work aims to enhance the efficiency and accessibility of PE diagnosis, ultimately improving patient outcomes.