Prostate Cancer Risk Stratification via Nondestructive 3D Pathology with Deep Learning–Assisted Gland Analysis

Prostate cancer treatment planning is largely dependent upon examination of core-needle biopsies. The microscopic architecture of the prostate glands forms the basis for prognostic grading by pathologists. Interpretation of these convoluted three-dimensional (3D) glandular structures via visual insp...

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Detalles Bibliográficos
Autores principales: Xie, Weisi, Reder, Nicholas P., Koyuncu, Can, Leo, Patrick, Hawley, Sarah, Huang, Hongyi, Mao, Chenyi, Postupna, Nadia, Kang, Soyoung, Serafin, Robert, Gao, Gan, Han, Qinghua, Bishop, Kevin W., Barner, Lindsey A., Fu, Pingfu, Wright, Jonathan L., Keene, C. Dirk, Vaughan, Joshua C., Janowczyk, Andrew, Glaser, Adam K., Madabhushi, Anant, True, Lawrence D., Liu, Jonathan T.C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for Cancer Research 2022
Materias:
Convergence and Technologies
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8803395/
https://www.ncbi.nlm.nih.gov/pubmed/34853071
http://dx.doi.org/10.1158/0008-5472.CAN-21-2843

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8803395/
https://www.ncbi.nlm.nih.gov/pubmed/34853071
http://dx.doi.org/10.1158/0008-5472.CAN-21-2843

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