Deep Learning with Quantitative Features of Magnetic Resonance Images to Predict Biochemical Recurrence of Radical Prostatectomy: A Multi-Center Study

SIMPLE SUMMARY: Biochemical recurrence after radical prostatectomy is vitally important for long-term oncological control and subsequent treatment of these patients. We applied radiomic technique to extract features from MR images of prostate cancer patients, and used deep learning algorithm to esta...

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Detalles Bibliográficos
Autores principales: Yan, Ye, Shao, Lizhi, Liu, Zhenyu, He, Wei, Yang, Guanyu, Liu, Jiangang, Xia, Haizhui, Zhang, Yuting, Chen, Huiying, Liu, Cheng, Lu, Min, Ma, Lulin, Sun, Kai, Zhou, Xuezhi, Ye, Xiongjun, Wang, Lei, Tian, Jie, Lu, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8234539/
https://www.ncbi.nlm.nih.gov/pubmed/34205786
http://dx.doi.org/10.3390/cancers13123098

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8234539/
https://www.ncbi.nlm.nih.gov/pubmed/34205786
http://dx.doi.org/10.3390/cancers13123098

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