Context-aware network for pulmonary nodule detection in CT images

Jiawei Zhang; Rushi Lan; Cheng Pang; Xiaonan Luo

doi:10.1117/12.2607212

28 October 2021 Context-aware network for pulmonary nodule detection in CT images

Jiawei Zhang, Rushi Lan, Cheng Pang, Xiaonan Luo

Proceedings Volume 11884, International Symposium on Artificial Intelligence and Robotics 2021; 118841X (2021) https://doi.org/10.1117/12.2607212
Event: International Symposium on Artificial Intelligence and Robotics 2021, 2021, Fukuoka, Japan

Abstract

Suffered from low resolution images and straightforward features, existing R-CNN based methods for pulmonary nodule detection usually fail in detecting objects with small scales. In this paper, we propose a novel context-aware network which takes the pulmonary regions and their neighbors for joint learning. The contextual cues of these regions reinforce each other, which is beneficial for the detection of small regions. Moreover, a set of redesigned anchors are used to adapted pulmonary nodules with various sizes. In order to avoid dilution by redundant samples specifying large nodules, a data enhancement strategy is implemented in the training stage by identifying hard samples. We test the proposed network on a dataset with 2000 lung images and demonstrate it performs well in detection of lung nodules with various sizes. The proposed method has 7% improved to the original Faster R-CNN.

Citation Download Citation

Jiawei Zhang, Rushi Lan, Cheng Pang, and Xiaonan Luo "Context-aware network for pulmonary nodule detection in CT images", Proc. SPIE 11884, International Symposium on Artificial Intelligence and Robotics 2021, 118841X (28 October 2021); https://doi.org/10.1117/12.2607212

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