Toward reliable automatic liver and tumor segmentation using convolutional neural network based on 2.5D models

PURPOSE: We investigated the parameter configuration in the automatic liver and tumor segmentation using a convolutional neural network based on 2.5D model. The implementation of 2.5D model shows promising results since it allows the network to have a deeper and wider network architecture while stil...

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Detalles Bibliográficos
Autores principales: Wardhana, Girindra, Naghibi, Hamid, Sirmacek, Beril, Abayazid, Momen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2020
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7822806/
https://www.ncbi.nlm.nih.gov/pubmed/33219906
http://dx.doi.org/10.1007/s11548-020-02292-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7822806/
https://www.ncbi.nlm.nih.gov/pubmed/33219906
http://dx.doi.org/10.1007/s11548-020-02292-y

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