Corpus ID: 212411339

Deep Learning on Point Clouds for False Positive Reduction at Nodule Detection in Chest CT Scans

@article{Drokin2020DeepLO,
  title={Deep Learning on Point Clouds for False Positive Reduction at Nodule Detection in Chest CT Scans},
  author={I. Drokin and Elena Ericheva},
  journal={ArXiv},
  year={2020},
  volume={abs/2005.03654}
}
This paper focuses on a novel approach for false-positive reduction (FPR) of nodule candidates in Computer-aided detection (CADe) systems following the suspicious lesions detection stage. Contrary to typical decisions in medical image analysis, the proposed approach considers input data not as a 2D or 3D image, but rather as a point cloud, and uses deep learning models for point clouds. We discovered that point cloud models require less memory and are faster both in training and inference… Expand
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References

SHOWING 1-10 OF 50 REFERENCES
A deep 3D residual CNN for false-positive reduction in pulmonary nodule detection.
  • 45
Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks
  • 620
Multi-view Convolutional Neural Network for lung nodule false positive reduction
  • 9
S4ND: Single-Shot Single-Scale Lung Nodule Detection
  • 47
  • PDF
An End-to-End Framework for Integrated Pulmonary Nodule Detection and False Positive Reduction
  • H. Tang, Xingwei Liu, X. Xie
  • Computer Science
  • 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)
  • 2019
  • 7
  • PDF
Automatic Pulmonary Nodule Detection in CT Scans Using Convolutional Neural Networks Based on Maximum Intensity Projection
  • 12
  • PDF
DeepLung: Deep 3D Dual Path Nets for Automated Pulmonary Nodule Detection and Classification
  • 162
  • PDF
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