Pulmonary Nodule Classification with Deep Convolutional Neural Networks on Computed Tomography Images

Computer aided detection (CAD) systems can assist radiologists by offering a second opinion on early diagnosis of lung cancer. Classification and feature representation play critical roles in false-positive reduction (FPR) in lung nodule CAD. We design a deep convolutional neural networks method for...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Wei, Cao, Peng, Zhao, Dazhe, Wang, Junbo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5192289/
https://www.ncbi.nlm.nih.gov/pubmed/28070212
http://dx.doi.org/10.1155/2016/6215085

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5192289/
https://www.ncbi.nlm.nih.gov/pubmed/28070212
http://dx.doi.org/10.1155/2016/6215085

Ejemplares similares