Deep neural network models for computational histopathology: A survey

CL Srinidhi, O Ciga, AL Martel - Medical image analysis, 2021 - Elsevier
Histopathological images contain rich phenotypic information that can be used to monitor
underlying mechanisms contributing to disease progression and patient survival outcomes …
被引用次数：553 相关文章

Deep neural network models for computational histopathology: A survey.

CL Srinidhi, O Ciga, AL Martel - Medical Image Analysis, 2020 - europepmc.org
Histopathological images contain rich phenotypic information that can be used to monitor
underlying mechanisms contributing to disease progression and patient survival outcomes …

[引用][C] Deep neural network models for computational histopathology: A survey

CL Srinidhi, O Ciga, AL Martel - Medical Image Analysis, 2021 - cir.nii.ac.jp
[HTML] nih.gov

[HTML][HTML] Deep neural network models for computational histopathology: A survey

CL Srinidhi, O Ciga, AL Martel - Medical image analysis, 2021 - ncbi.nlm.nih.gov
Histopathological images contain rich phenotypic information that can be used to monitor
underlying mechanisms contributing to disease progression and patient survival outcomes …

Deep neural network models for computational histopathology: A survey

CL Srinidhi, O Ciga, AL Martel - arXiv preprint arXiv:1912.12378, 2019 - arxiv.org
Histopathological images contain rich phenotypic information that can be used to monitor
underlying mechanisms contributing to diseases progression and patient survival outcomes …

Deep neural network models for computational histopathology: A survey

CL Srinidhi, O Ciga, AL Martel - Medical image analysis, 2021 - pubmed.ncbi.nlm.nih.gov
Histopathological images contain rich phenotypic information that can be used to monitor
underlying mechanisms contributing to disease progression and patient survival outcomes …

Deep neural network models for computational histopathology: A survey

CL Srinidhi, O Ciga, AL Martel - arXiv e-prints, 2019 - ui.adsabs.harvard.edu
Histopathological images contain rich phenotypic information that can be used to monitor
underlying mechanisms contributing to diseases progression and patient survival outcomes …