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http://hdl.handle.net/10397/88798
Title: | Towards accurate pulmonary nodule detection by representing nodules as points with high-resolution network | Authors: | Gong, ZH Li, D Lin, JT Zhang, Y Lam, KM |
Issue Date: | 2020 | Source: | IEEE access, . . 2020, , v. 8, p. 157391-157402 | Abstract: | Almost all successful nodule detectors rely heavily on a fixed set of anchor boxes. In this paper, inspired by the success of the keypoint estimation method in natural image detection, we propose an anchor-free framework for accurate pulmonary nodule detection. We first present a novel representation for detecting nodules, in terms of their 3D center locations, which reduces the number of hyper-parameters and the corresponding computation related to anchors, thus making the nodule detection pipeline much simpler. Then, an effective two-stream network is introduced to reduce the false positive nodule candidates, by aggregating information from the image stream and motion-history stream. Experiments show that the proposed approach achieves a sensitivity of 96.1%, with 8 false positives per scan, and a CPM score of 90.6%, on the publicly available LUNA16 dataset, which outperforms other state-of-the-art methods. By testing on the SPIE-AAPM dataset with models pre-trained on the LUNA16, our proposed method yields 92.8% sensitivity with 8 false positives per scan. This demonstrates the effectiveness and generalization ability of our method. | Keywords: | Three-Dimensional displays Feature extraction Detectors Two dimensional displays Estimation Sensitivity Lung Lung nodule detection 3D convolution neural network Keypoint estimation |
Publisher: | Institute of Electrical and Electronics Engineers | Journal: | IEEE access | EISSN: | 2169-3536 | DOI: | 10.1109/ACCESS.2020.3019104 | Rights: | This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ The following publication Gong, Z. H., Li, D., Lin, J. T., Zhang, Y., & Lam, K. M. (2020). Towards accurate pulmonary nodule detection by representing nodules as points with high-resolution network. IEEE Access, 8, 157391-157402 is available at https://dx.doi.org/10.1109/ACCESS.2020.3019104 |
Appears in Collections: | Journal/Magazine Article |
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Gong_Accurate_Pulmonary_Nodule.pdf | 2.46 MB | Adobe PDF | View/Open |
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