Comparing efficiency of an attention-based deep learning network with contemporary radiological workflow for pulmonary embolism detection on CTPA: A retrospective study

Comparing efficiency of an attention-based deep learning network with contemporary radiological workflow for pulmonary embolism detection on CTPA: A retrospective study

Rational and objectives: Pulmonary embolism (PE) is the third most fatal cardiovascular disease in the United States. Currently, Computed Tomography Pulmonary Angiography (CTPA) serves as diagnostic gold standard for detecting PE. However, its efficacy is limited by factors such as contrast bolus ti...

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Bibliographic Details
Main Authors: Gagandeep Singh, Annie Singh, Tejasvi Kainth, Sudhir Suman, Nicole Sakla, Luke Partyka, Tej Phatak, Prateek Prasanna
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:European Journal of Radiology Open
Subjects:
Pulmonary Embolism
Deep learning
Neural Network
Computed Tomography Pulmonary Angiogram (CTPA)
Medical images
Radiology
Online Access:http://www.sciencedirect.com/science/article/pii/S2352047725000243
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