Structured learning algorithm for detection of nonobstructive and obstructive coronary plaque lesions from computed tomography angiography

@article{Kang2015StructuredLA,
  title={Structured learning algorithm for detection of nonobstructive and obstructive coronary plaque lesions from computed tomography angiography},
  author={Dongwoo Kang and Damini Dey and Piotr J. Slomka and Reza Arsanjani and Ryo Nakazato and Hyunsuk Ko and Daniel S. Berman and Debiao Li and C.-C. Jay Kuo},
  journal={Journal of Medical Imaging},
  year={2015},
  volume={2}
}
Abstract. Visual identification of coronary arterial lesion from three-dimensional coronary computed tomography angiography (CTA) remains challenging. We aimed to develop a robust automated algorithm for computer detection of coronary artery lesions by machine learning techniques. A structured learning technique is proposed to detect all coronary arterial lesions with stenosis ≥25%. Our algorithm consists of two stages: (1) two independent base decisions indicating the existence of lesions in… 

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