False Positive Reduction in Lung GGO Nodule Detection with 3D Volume Shape Descriptor

@article{Yang2007FalsePR,
  title={False Positive Reduction in Lung GGO Nodule Detection with 3D Volume Shape Descriptor},
  author={Ming Yang and Senthil Periaswamy and Ying Wu},
  journal={2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07},
  year={2007},
  volume={1},
  pages={I-437-I-440}
}
Lung nodule detection, especially ground glass opacity (GGO) detection, in helical computed tomography (CT) images is a challenging computer-aided detection (CAD) task due to the enormous variances in nodules' volumes, shapes, appearances, and the structures nearby. Most of the detection algorithms employ some efficient candidate generation (CG) algorithms to spot the suspicious volumes with high sensitivity at the cost of low specificity, e.g. tens even hundreds of false positives per volume… CONTINUE READING

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