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Info: This is version 2 of the TotalSegmentator dataset.In 1228 CT images we segmented 117 anatomical structures covering a majority of relevant classes for most use cases. The CT images were randomly sampled from clinical routine, thus representing a real world dataset which generalizes to clinical application. The dataset contains a wide range of different pathologies, scanners, sequences and institutions. Link to a copy of this dataset on Dropbox for much quicker download: Dropbox Link Overview of differences to v1 of this dataset: here A small subset of this dataset with only 102 subjects for quick download+exploration can be found here: here You can find a segmentation model trained on this dataset here.More details about the dataset can be found in the corresponding paper (the paper describes v1 of the dataset). Please cite this paper if you use the dataset. This dataset was created by the department of Research and Analysis at University Hospital Basel. UPDATE: On 2023-10-27 we uploaded version 2.0.1 which fixes broken files.
CT image, medical image segmentation, deep learning, organ segmentation
CT image, medical image segmentation, deep learning, organ segmentation
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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downloads | 1K |