Corpus ID: 203836100

Pi-PE: A Pipeline for Pulmonary Embolism Detection using Sparsely Annotated 3D CT Images

@article{Rajan2019PiPEAP,
  title={Pi-PE: A Pipeline for Pulmonary Embolism Detection using Sparsely Annotated 3D CT Images},
  author={Deepta Rajan and David J. Beymer and Shafiq Abedin and Ehsan Dehghan},
  journal={ArXiv},
  year={2019},
  volume={abs/1910.02175}
}
Pulmonary embolisms (PE) are known to be one of the leading causes for cardiac-related mortality. Due to inherent variabilities in how PE manifests and the cumbersome nature of manual diagnosis, there is growing interest in leveraging AI tools for detecting PE. In this paper, we build a two-stage detection pipeline that is accurate, computationally efficient, robust to variations in PE types and kernels used for CT reconstruction, and most importantly, does not require dense annotations. Given… Expand
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