Automatic detection of pulmonary nodules on CT images with YOLOv3: development and evaluation using simulated and patient data | Zendy

Chenyang Liu | Zendy; Shen-Chiang Hu | Zendy; Chunhao Wang | Zendy; Kyle Lafata | Zendy; F Yin | Zendy

Open Access

Automatic detection of pulmonary nodules on CT images with YOLOv3: development and evaluation using simulated and patient data

Author(s) -

Chenyang Liu,

Shen-Chiang Hu,

Chunhao Wang,

Kyle Lafata,

F Yin

Publication year - 2020

Publication title -

quantitative imaging in medicine and surgery

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.766

H-Index - 21

eISSN - 2223-4292

pISSN - 2223-4306

DOI - 10.21037/qims-19-883

Subject(s) - cad , computer science , artificial intelligence , ground truth , convolutional neural network , false positive paradox , computer aided diagnosis , pattern recognition (psychology) , feature (linguistics) , imaging phantom , nodule (geology) , receiver operating characteristic , computer vision , nuclear medicine , medicine , machine learning , paleontology , linguistics , philosophy , engineering drawing , engineering , biology

To develop a high-efficiency pulmonary nodule computer-aided detection (CAD) method for localization and diameter estimation.

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