Deep Volumetric Universal Lesion Detection using Light-Weight Pseudo 3D Convolution and Surface Point Regression

@article{Cai2020DeepVU,
  title={Deep Volumetric Universal Lesion Detection using Light-Weight Pseudo 3D Convolution and Surface Point Regression},
  author={Jinzheng Cai and Ke Yan and Chi-Tung Cheng and Jing Xiao and C. Liao and Le Lu and Adam P. Harrison},
  journal={ArXiv},
  year={2020},
  volume={abs/2008.13254}
}
Identifying, measuring and reporting lesions accurately and comprehensively from patient CT scans are important yet time-consuming procedures for physicians. Computer-aided lesion/significant-findings detection techniques are at the core of medical imaging, which remain very challenging due to the tremendously large variability of lesion appearance, location and size distributions in 3D imaging. In this work, we propose a novel deep anchor-free one-stage volumetric lesion detector (VLD… Expand

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