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arXiv · 2006.14215

Deep Residual 3D U-Net for Joint Segmentation and Texture Classification of Nodules in Lung

Alexandr G. Rassadin
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Abstract

In this work we present a method for lung nodules segmentation, their texture classification and subsequent follow-up recommendation from the CT image of lung. Our method consists of neural network model based on popular U-Net architecture family but modified for the joint nodule segmentation and its texture classification tasks and an ensemble-based model for the follow-up recommendation. This solution was evaluated within the LNDb medical imaging challenge and produced the best nodule segmentation result on the final leaderboard.

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Alexandr G. Rassadin. 2020-06-26. Deep Residual 3D U-Net for Joint Segmentation and Texture Classification of Nodules in Lung. https://doi.org/10.1007/978-3-030-50516-5_37

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