SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-Rays

@inproceedings{Dai2018SCANSC,
  title={SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-Rays},
  author={Wei Dai and Nanqing Dong and Zeya Wang and Xiaodan Liang and Hao Zhang and Eric P. Xing},
  booktitle={DLMIA/ML-CDS@MICCAI},
  year={2018}
}
Chest X-ray (CXR) is one of the most commonly prescribed medical imaging procedures, often with over 2– 10x more scans than other imaging modalities such as MRI, CT scan, and PET scans. These voluminous CXR scans place significant workloads on radiologists and medical practitioners. Organ segmentation is a crucial step to obtain effective computer-aided detection on CXR. In this work, we propose Structure Correcting Adversarial Network (SCAN) to segment lung fields and the heart in CXR images… CONTINUE READING
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