An automated lung segmentation approach using bidirectional chain codes to improve nodule detection accuracy

@article{Shen2015AnAL,
  title={An automated lung segmentation approach using bidirectional chain codes to improve nodule detection accuracy},
  author={Shiwen Shen and Alex A. T. Bui and Jason Cong and William Hsu},
  journal={Computers in biology and medicine},
  year={2015},
  volume={57},
  pages={
          139-49
        }
}
Computer-aided detection and diagnosis (CAD) has been widely investigated to improve radiologists' diagnostic accuracy in detecting and characterizing lung disease, as well as to assist with the processing of increasingly sizable volumes of imaging. [...] Key ResultSegmentation accuracy was further validated on 10 randomly selected CT series, finding a 0.3% average over-segmentation ratio and 2.4% under-segmentation rate when compared to manually segmented reference standards done by an expert. Expand Abstract

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