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Author:

Jian, Muwei (Jian, Muwei.) | Huang, Huihui (Huang, Huihui.) | Zhang, Haoran (Zhang, Haoran.) | Wang, Rui (Wang, Rui.) | Li, Xiaoguang (Li, Xiaoguang.) | Yu, Hui (Yu, Hui.)

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Abstract:

Lung cancer stands as the leading cause of cancer related mortality worldwide. Precise and automated identification of lung nodules through 3D Computed Tomography (CT) scans is an essential part of screening for lung cancer effectively. Due to the small size of pulmonary nodules and the close correlation between neighboring slices of 3D CT images, most of the existing methods only consider the characteristics of a single slice, thus easily lead to insufficient detection accuracy of pulmonary nodules. To solve this problem, this paper proposes a Channel Shuffle Slice-Aware Network (CSSANet), which aims to fully exploit the spatial correlation between slices and effectively utilize the intra-slice features and inter-slice contextual information to achieve accurate detection of lung nodules. Specifically, we design a Group Shuffle Attention module (GSA module) to fuse the inter-slice feature in order to enhance the discrimination and extraction of corresponding shape information of distinct nodules in the same group of slices. Experiments and ablation study on a publicly available LUNA16 dataset demonstrate that the proposed method can enhance the detection sensitivity effectively. The Competition Performance Metric (CPM) score of 89.8 % is superior over other representative detection models. © 2024

Keyword:

Pulmonary diseases Lung cancer Image correlation Diagnosis Computerized tomography

Author Community:

  • [ 1 ] [Jian, Muwei]School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, China
  • [ 2 ] [Jian, Muwei]School of Information Science and Engineering, Linyi University, Linyi, China
  • [ 3 ] [Huang, Huihui]School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, China
  • [ 4 ] [Huang, Huihui]cSCAN, University of Glasgow, Glasgow; G12 8QB, United Kingdom
  • [ 5 ] [Zhang, Haoran]School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, China
  • [ 6 ] [Wang, Rui]School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, China
  • [ 7 ] [Li, Xiaoguang]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 8 ] [Yu, Hui]cSCAN, University of Glasgow, Glasgow; G12 8QB, United Kingdom

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Source :

Neurocomputing

ISSN: 0925-2312

Year: 2025

Volume: 615

6 . 0 0 0

JCR@2022

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ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 1

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