1 to 8 of 8 Results
Aug 2, 2022
Brumer, Irene, 2022, "Synthetic renal ASL MRI [data]", https://doi.org/10.11588/data/QAHWSF, heiDATA, V1
Synthetic renal ASL data sets simulating in-vivo acquisitions were generated using body models from the XCAT phantom, the general kinetic model and literature values for tissue properties. Sequence and ASL parameters were set in accordance with the current renal ASL consensus. Fi... |
Aug 2, 2022 -
Synthetic renal ASL MRI [data]
ZIP Archive - 37.2 MB -
MD5: c1a01a571869bc6cb31ad03ec13b2c21
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Jul 14, 2022
Zöllner, Frank, 2022, "Synthesis of CT images from digital body phantoms using CycleGAN [dataset]", https://doi.org/10.11588/data/7NRFYC, heiDATA, V1
The potential of medical image analysis with neural networks is limited by the restricted availability of extensive data sets. The incorporation of synthetic training data is one approach to bypass this shortcoming, as synthetic data offer accurate annotations and unlimited data... |
ZIP Archive - 49.8 GB -
MD5: 0c9ad5cd6faab738d35e933aef0e4619
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Jun 22, 2022
Zöllner, Frank, 2022, "Multimodal ground truth datasets for abdominal medical image registration [data]", https://doi.org/10.11588/data/ICSFUS, heiDATA, V1
Sparsity of annotated data is a major limitation in medical image processing tasks such as registration. Registered multimodal image data are essential for the diagnosis of medical conditions and the success of interventional medical procedures. To overcome the shortage of data,... |
ZIP Archive - 25.4 GB -
MD5: 5827c4d57139e094fd58b32417b8b436
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ZIP Archive - 2.8 GB -
MD5: d68291bee7870146b4c72ea475a23a67
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ZIP Archive - 3.5 GB -
MD5: 7ecd9b894710d6269f28e63d4e668b57
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