Fully automated segmentation and radiomics feature extraction of hypopharyngeal cancer on MRI using deep learning

OBJECTIVES: To use convolutional neural network for fully automated segmentation and radiomics features extraction of hypopharyngeal cancer (HPC) tumor in MRI. METHODS: MR images were collected from 222 HPC patients, among them 178 patients were used for training, and another 44 patients were recrui...

Descripción completa

Detalles Bibliográficos
Autores principales: Lin, Yu-Chun, Lin, Gigin, Pandey, Sumit, Yeh, Chih-Hua, Wang, Jiun-Jie, Lin, Chien-Yu, Ho, Tsung-Ying, Ko, Sheung-Fat, Ng, Shu-Hang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Imaging Informatics and Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415433/
https://www.ncbi.nlm.nih.gov/pubmed/37338554
http://dx.doi.org/10.1007/s00330-023-09827-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415433/
https://www.ncbi.nlm.nih.gov/pubmed/37338554
http://dx.doi.org/10.1007/s00330-023-09827-2

Ejemplares similares