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381 to 390 of 511 Results
tumor_class_pve_1.nii.gz
Dec 17, 2024 - Onco* tutorial
Gzip Archive - 288.7 KB - MD5: 10ff06c6201ce1be3d62443ad357b6d9
tumor_class_pve_2.nii.gz
Dec 17, 2024 - Onco* tutorial
Gzip Archive - 203.6 KB - MD5: 905f0d49a636a33aa2c131992d9ed852
white_matter.h5
Dec 17, 2024 - Onco* tutorial
Hierarchical Data Format - 6.8 MB - MD5: a30b2007f58c7976a9966e6b00f88759
white_matter.xdmf
Dec 17, 2024 - Onco* tutorial
Unknown - 773 B - MD5: 590bb88f4bb23178e81cf4f4600c17e5
wm.nii.gz
Dec 17, 2024 - Onco* tutorial
Gzip Archive - 682.7 KB - MD5: 7196ef2d254d274c9fae3bde982a9eac
OncoTUM models
Dec 16, 2024
Suditsch, Marlon; Wagner, Arndt; Ricken, Tim, 2024, "OncoTUM models", https://doi.org/10.18419/DARUS-4647, DaRUS, V1
OncoTUM models This repository hosts pretrained neural network models for OncoTUM, a key software package within the umbrella project Onco* for modelling and numerical simulations of tumours. OncoTUM is designed to facilitate tumour segmentations from medical images, leveraging state-of-the-art deep learning techniques. Purpose The pretrained model...
0_im.nii.gz
Dec 16, 2024 - OncoTUM models
Gzip Archive - 34.0 KB - MD5: 91ce61bafac37076f37555d587cbb713
hyperparam.yaml
Dec 16, 2024 - OncoTUM models
Unknown - 416 B - MD5: 16d97c4a2f33b4c17d2f3af41a8b87eb
hyperparam.yaml
Dec 16, 2024 - OncoTUM models
Unknown - 414 B - MD5: 91cdff26727ba28fb8794dfe3177db0c
hyperparam.yaml
Dec 16, 2024 - OncoTUM models
Unknown - 437 B - MD5: 660c4d380a690f173e7315ba7121b3d8
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