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

• URL: http://arxiv.org/abs/2006.14215v2
• Date: Fri, 26 Jun 2020 05:08:18 GMT
• Title: Deep Residual 3D U-Net for Joint Segmentation and Texture Classification of Nodules in Lung
• Authors: Alexandr G. Rassadin
• Abstract summary: 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.
• Score: 91.3755431537592
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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