Quick guide on radiology image pre-processing for deep learning applications in prostate cancer research

Purpose: Deep learning has achieved major breakthroughs during the past decade in almost every field. There are plenty of publicly available algorithms, each designed to address a different task of computer vision in general. However, most of these algorithms cannot be directly applied to images in...

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Detalles Bibliográficos
Autores principales: Masoudi, Samira, Harmon, Stephanie A., Mehralivand, Sherif, Walker, Stephanie M., Raviprakash, Harish, Bagci, Ulas, Choyke, Peter L., Turkbey, Baris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Photo-Optical Instrumentation Engineers 2021
Materias:
Review Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7790158/
https://www.ncbi.nlm.nih.gov/pubmed/33426151
http://dx.doi.org/10.1117/1.JMI.8.1.010901

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7790158/
https://www.ncbi.nlm.nih.gov/pubmed/33426151
http://dx.doi.org/10.1117/1.JMI.8.1.010901

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