期刊
BIOMEDICAL OPTICS EXPRESS
卷 3, 期 11, 页码 2809-2824出版社
OPTICAL SOC AMER
DOI: 10.1364/BOE.3.002809
关键词
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资金
- National Heart, Lung, and Blood Institute through NIH [R21HL108263]
- National Center for Research Resources
- National Center for Advancing Translational Sciences, National Institutes of Health [UL1RR024989]
- Chinese Government
- American Heart Association [11PRE7320034]
Intravascular optical coherence tomography (iOCT) is being used to assess viability of new coronary artery stent designs. We developed a highly automated method for detecting stent struts and measuring tissue coverage. We trained a bagged decision trees classifier to classify candidate struts using features extracted from the images. With 12 best features identified by forward selection, recall (precision) were 90%-94% (85%-90%). Including struts deemed insufficiently bright for manual analysis, precision improved to 94%. Strut detection statistics approached variability of manual analysis. Differences between manual and automatic area measurements were 0.12 +/- 0.20 mm(2) and 0.11 +/- 0.20 mm(2) for stent and tissue areas, respectively. With proposed algorithms, analyst time per stent should significantly reduce from the 6-16 hours now required. (C) 2012 Optical Society of America
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