Development of U-Net Breast Density Segmentation Method for Fat-Sat MR Images Using Transfer Learning Based on Non-Fat-Sat Model

To develop a U-net deep learning method for breast tissue segmentation on fat-sat T1-weighted (T1W) MRI using transfer learning (TL) from a model developed for non-fat-sat images. The training dataset (N = 126) was imaged on a 1.5 T MR scanner, and the independent testing dataset (N = 40) was imaged...

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Detalles Bibliográficos
Autores principales: Zhang, Yang, Chan, Siwa, Chen, Jeon-Hor, Chang, Kai-Ting, Lin, Chin-Yao, Pan, Huay-Ben, Lin, Wei-Ching, Kwong, Tiffany, Parajuli, Ritesh, Mehta, Rita S., Chien, Sou-Hsin, Su, Min-Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8455741/
https://www.ncbi.nlm.nih.gov/pubmed/34244879
http://dx.doi.org/10.1007/s10278-021-00472-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8455741/
https://www.ncbi.nlm.nih.gov/pubmed/34244879
http://dx.doi.org/10.1007/s10278-021-00472-z

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