Carregando...

Deep learning for liver tumor diagnosis part II: convolutional neural network interpretation using radiologic imaging features

OBJECTIVES: To develop a proof-of-concept “interpretable” deep learning prototype that justifies aspects of its predictions from a pre-trained hepatic lesion classifier. METHODS: A convolutional neural network (CNN) was engineered and trained to classify six hepatic tumor entities using 494 lesions...

ver descrição completa

Na minha lista:
Detalhes bibliográficos
Publicado no:Eur Radiol
Principais autores: Wang, Clinton J., Hamm, Charlie A., Savic, Lynn J., Ferrante, Marc, Schobert, Isabel, Schlachter, Todd, Lin, MingDe, Weinreb, Jeffrey C., Duncan, James S., Chapiro, Julius, Letzen, Brian
Formato: Artigo
Idioma:Inglês
Publicado em: 2019
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7243989/
https://ncbi.nlm.nih.gov/pubmed/31093705
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00330-019-06214-8
Tags: Adicionar Tag
Sem tags, seja o primeiro a adicionar uma tag!