EDICNet: An end-to-end detection and interpretable malignancy classification network for pulmonary nodules in computed tomography

We present an interpretable end-to-end computer-aided detection and diagnosis tool for pulmonary nodules on computed tomography (CT) using deep learning-based methods. The proposed network consists of a nodule detector and a nodule malignancy classifier. We used RetinaNet to train a nodule detector...

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Bibliographic Details
Published in:Proc SPIE Int Soc Opt Eng
Main Authors: Lin, Yannan, Wei, Leihao, Han, Simon X., Aberle, Denise R., Hsu, William
Format: Artigo
Language:Inglês
Published: 2020
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Article
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC7325481/
https://ncbi.nlm.nih.gov/pubmed/32606487
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/12.2551220
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