Institute of Pathology Mannheim

Data publications from the Institute of Pathology Mannheim at the Medical Faculty Mannheim (Heidelberg University).

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41 to 50 of 71 Results

train_longHE.zip Jul 27, 2021 - Normalization of HE-Stained Histological Images using Cycle Consistent Generative Adversarial Networks [Dataset] ZIP Archive - 3.7 GB - MD5: fb27263c6f7b96b4cd118bff95229be2
train_onlyE.zip Jul 27, 2021 - Normalization of HE-Stained Histological Images using Cycle Consistent Generative Adversarial Networks [Dataset] ZIP Archive - 2.8 GB - MD5: 711fc1b987b5a0d8312f5727a2edde15
train_onlyH.zip Jul 27, 2021 - Normalization of HE-Stained Histological Images using Cycle Consistent Generative Adversarial Networks [Dataset] ZIP Archive - 3.8 GB - MD5: ca25fcb98acaccccca6e3864f78359c6
train_shortHE.zip Jul 27, 2021 - Normalization of HE-Stained Histological Images using Cycle Consistent Generative Adversarial Networks [Dataset] ZIP Archive - 3.5 GB - MD5: 4486f2d7c5e908cf0bec2ba857e059bf
tumorLymphnode_patches.zip Jul 27, 2021 - Normalization of HE-Stained Histological Images using Cycle Consistent Generative Adversarial Networks [Dataset] ZIP Archive - 484.6 MB - MD5: 5ca5dcacd937be80d606597dcc878f7e
Assessment of glomerular morphological patterns by deep learning algorithms [Research Data] Feb 7, 2022 Weis, Cleo-Aron, 2022, "Assessment of glomerular morphological patterns by deep learning algorithms [Research Data]", https://doi.org/10.11588/data/JWZ2CK, heiDATA, V1 Test data and models to the paper "Assessment of glomerular morphological patterns by deep learning algorithms". Different, from other groups, defined CNN-models (saved as .pt-files) are trained to identify nine predefined patterns of glomerular changes. The models are: AlexNet [...
model_alex.pt Feb 7, 2022 - Assessment of glomerular morphological patterns by deep learning algorithms [Research Data] Unknown - 221.5 MB - MD5: 9dc706ae346e67dc1bafd73159279e6c
model_densenet121.pt Feb 7, 2022 - Assessment of glomerular morphological patterns by deep learning algorithms [Research Data] Unknown - 27.1 MB - MD5: 784a68762bf7f8cf8d68e68dd34178c6
model_inception.pt Feb 7, 2022 - Assessment of glomerular morphological patterns by deep learning algorithms [Research Data] Unknown - 96.2 MB - MD5: 84f74583b9067e6641f698be0610cf81
model_ResNet101.pt Feb 7, 2022 - Assessment of glomerular morphological patterns by deep learning algorithms [Research Data] Unknown - 162.8 MB - MD5: 282550f75a2e09a0714cb537fdb7cd00

train_longHE.zip

Jul 27, 2021 - Normalization of HE-Stained Histological Images using Cycle Consistent Generative Adversarial Networks [Dataset]

ZIP Archive - 3.7 GB -

train_onlyE.zip

Jul 27, 2021 - Normalization of HE-Stained Histological Images using Cycle Consistent Generative Adversarial Networks [Dataset]

ZIP Archive - 2.8 GB -

train_onlyH.zip

Jul 27, 2021 - Normalization of HE-Stained Histological Images using Cycle Consistent Generative Adversarial Networks [Dataset]

ZIP Archive - 3.8 GB -

train_shortHE.zip

Jul 27, 2021 - Normalization of HE-Stained Histological Images using Cycle Consistent Generative Adversarial Networks [Dataset]

ZIP Archive - 3.5 GB -

tumorLymphnode_patches.zip

Jul 27, 2021 - Normalization of HE-Stained Histological Images using Cycle Consistent Generative Adversarial Networks [Dataset]

ZIP Archive - 484.6 MB -

Assessment of glomerular morphological patterns by deep learning algorithms [Research Data]

Feb 7, 2022

Weis, Cleo-Aron, 2022, "Assessment of glomerular morphological patterns by deep learning algorithms [Research Data]", https://doi.org/10.11588/data/JWZ2CK, heiDATA, V1

Test data and models to the paper "Assessment of glomerular morphological patterns by deep learning algorithms". Different, from other groups, defined CNN-models (saved as .pt-files) are trained to identify nine predefined patterns of glomerular changes. The models are: AlexNet [...

model_alex.pt

Feb 7, 2022 - Assessment of glomerular morphological patterns by deep learning algorithms [Research Data]

Unknown - 221.5 MB -

model_densenet121.pt

Feb 7, 2022 - Assessment of glomerular morphological patterns by deep learning algorithms [Research Data]

Unknown - 27.1 MB -

model_inception.pt

Feb 7, 2022 - Assessment of glomerular morphological patterns by deep learning algorithms [Research Data]

Unknown - 96.2 MB -

model_ResNet101.pt

Feb 7, 2022 - Assessment of glomerular morphological patterns by deep learning algorithms [Research Data]

Unknown - 162.8 MB -

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