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Lung Nodule Malignancy Classification Integrating Deep and Radiomic Features in a Three-Way Attention-Based Fusion Module

Author(s): Khademi S; Heidarian S; Afshar P; Mohammadi A; Sidiqi A; Nguyen ET; Ganeshan B; Oikonomou A;

In this study, we propose a novel hybrid framework for assessing the invasiveness of an in-house dataset of 114 pathologically proven lung adenocarcinomas presenting as subsolid nodules on Computed Tomography (CT). Nodules were classified into group 1 (G1), which included atypical adenomatous hyp ...

Article GUID: 41150036


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