Cargando…
Prostate Cancer Detection using Deep Convolutional Neural Networks
Prostate cancer is one of the most common forms of cancer and the third leading cause of cancer death in North America. As an integrated part of computer-aided detection (CAD) tools, diffusion-weighted magnetic resonance imaging (DWI) has been intensively studied for accurate detection of prostate c...
Autores principales: | Yoo, Sunghwan, Gujrathi, Isha, Haider, Masoom A., Khalvati, Farzad |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6925141/ https://www.ncbi.nlm.nih.gov/pubmed/31863034 http://dx.doi.org/10.1038/s41598-019-55972-4 |
Ejemplares similares
-
A Modified AUC for Training Convolutional Neural Networks: Taking Confidence Into Account
por: Namdar, Khashayar, et al.
Publicado: (2021) -
Automated prostate cancer detection via comprehensive multi-parametric magnetic resonance imaging texture feature models
por: Khalvati, Farzad, et al.
Publicado: (2015) -
MPCaD: a multi-scale radiomics-driven framework for automated prostate cancer localization and detection
por: Khalvati, Farzad, et al.
Publicado: (2018) -
Radiomics Driven Diffusion Weighted Imaging Sensing Strategies for Zone-Level Prostate Cancer Sensing
por: Dulhanty, Chris, et al.
Publicado: (2020) -
Improving prognostic performance in resectable pancreatic ductal adenocarcinoma using radiomics and deep learning features fusion in CT images
por: Zhang, Yucheng, et al.
Publicado: (2021)