Article

A Bayesian TransUNet for Uncertainty-AwareSegmentation of Pulmonary Nodules in CT Scans

2026-05-22

Abstract excerpt

<title>Abstract</title> <p>Lung cancer screening via computed tomography generates vast amounts of image data, driving the need for automated and reliable segmentation of pulmonary nodules. Deep learning models often lack the ability to quantify prediction uncertainty, which is crucial for clinical trust. This study presents a Bayesian TransUNet framework that segments pulmonary nodules while estimating both epis...

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Literature Corpus work: 4826aa05-5451-53b9-a12a-862fc7d4e7a7
DOI: 10.21203/rs.3.rs-8837540/v1

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