COPD-FlowNet: Elevating Non-invasive COPD Diagnosis with CFD Simulations

• URL: http://arxiv.org/abs/2312.11561v1
• Date: Sun, 17 Dec 2023 15:09:20 GMT
• Title: COPD-FlowNet: Elevating Non-invasive COPD Diagnosis with CFD Simulations
• Authors: Aryan Tyagi, Aryaman Rao, Shubhanshu Rao, Raj Kumar Singh
• Abstract summary: COPDFlowNet generates synthetic Computational Fluid Dynamics (CFD) velocity flow field images specific to the trachea of COPD patients. COPDFlowNet incorporates a custom Convolutional Neural Network (CNN) architecture to predict the location of the obstruction site.
• Score: 0.9012198585960443
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Chronic Obstructive Pulmonary Disorder (COPD) is a prevalent respiratory disease that significantly impacts the quality of life of affected individuals. This paper presents COPDFlowNet, a novel deep-learning framework that leverages a custom Generative Adversarial Network (GAN) to generate synthetic Computational Fluid Dynamics (CFD) velocity flow field images specific to the trachea of COPD patients. These synthetic images serve as a valuable resource for data augmentation and model training. Additionally, COPDFlowNet incorporates a custom Convolutional Neural Network (CNN) architecture to predict the location of the obstruction site.

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