Probabilistic 3D Polyp Detection in CT Images: The Role of Sample Alignment

@article{Tu2006Probabilistic3P,
  title={Probabilistic 3D Polyp Detection in CT Images: The Role of Sample Alignment},
  author={Zhuowen Tu and Xiang Sean Zhou and Luca Bogoni and Adrian Barbu and Dorin Comaniciu},
  journal={2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06)},
  year={2006},
  volume={2},
  pages={1544-1551}
}
Automatic polyp detection is an increasingly important task in medical imaging with virtual colonoscopy [15] being widely used. In this paper, we present a 3D object detection algorithm and show its application on polyp detection from CT images. We make the following contributions: (1) The system adopts Probabilistic Boosting Tree (PBT) to probabilistically detect polyps. Integral volume and 3D Haar filters are introduced to achieve fast feature computation. (2) We give an explicit convergence… CONTINUE READING