Multi-Scanner Canine Cutaneous Squamous Cell Carcinoma Histopathology Dataset
Creators
- 1. Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- 2. Freie Universität Berlin, Berlin, Germany
- 3. Institute of Pathology, University of Veterinary Medicine, Vienna, Austria
- 4. Pathology Department, University Medical Centre Utrecht, The Netherlands
- 5. echnische Hochschule Ingolstadt, Ingolstadt, Germany
Description
This is a multi-scanner version of the SCC subset of the publicly available CATCH dataset (https://doi.org/10.7937/TCIA.2M93-FX66). The dataset contains 44 samples digitized with five slide scanning systems (220 images) :
- Aperio ScanScope CS2 (Leica, Germany), resolution: 0.25 µm/pixel
- NanoZoomer S210 (Hamamatsu, Japan), resolution: 0.22 µm/pixel
- NanoZoomer 2.0-HT (Hamamatsu, Japan), resolution: 0.23 µm/pixel
- Pannoramic 1000 (3DHISTECH, Hungary), resolution: 0.25 µm/pixel
- Aperio GT 450 (Leica, Germany), resolution: 0.26 µm/pixel
All Aperio ScanScope CS2 whole slide images were manually annotated for tumor and six skin tissue classes (epidermis, dermis, subcutis, bone, cartilage, and a combined class of inflammation and necrosis). All 1,243 polygon annotations were transferred to the remaining four scanners and are provided as MS COCO JSON and as SQLITE database (SlideRunner format). Due to size restrictions on Zenodo, we provide the files as lower-resolution pyramidal TIFFs (4 µm/pixel).
If you use the dataset for research purposes, please cite our paper:
Frauke Wilm, Marco Fragoso, Christof A. Bertram, Nikolas Stathonikos, Mathias Öttl, Jingna Qiu, Robert Klopfleisch, Andreas Maier, Katharina Breininger, and Marc Aubreville, "Multi-Scanner Canine Cutaneous Squamous Cell Carcinoma Histopathology Dataset", 2023, https://arxiv.org/abs/2301.04423
Files
scc.json
Files
(12.1 GB)
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md5:366230a755b1e7f0bb5fd591f935f8cc
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97.1 MB | Preview Download |
md5:1003a70197a1213c9d361da6f0c13f80
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108.5 MB | Preview Download |
md5:6b336642b988a30e40432458b7435d32
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68.0 MB | Preview Download |
md5:3f820a8db9fabf0001b9a5f81407cc57
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94.4 MB | Preview Download |
md5:f40cba3825c1399e77008ae5ee05387c
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73.1 MB | Preview Download |
md5:f4644045a0087cbe4c154983b33532b1
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116.9 MB | Preview Download |
md5:bfe28b1b8f4998f0cec2e20d192a96d1
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130.3 MB | Preview Download |
md5:5d47a942d4b930cceaa8e50edc2aae99
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72.8 MB | Preview Download |
md5:fa669d6b755f2712e9f984cc422cf416
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84.6 MB | Preview Download |
md5:fadd75e3e1e02fdd73a762eed387ccd3
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72.1 MB | Preview Download |
md5:2ab985964e5401d369a75ed8832f2554
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108.2 MB | Preview Download |
md5:d5171a09d523042c201b4f136ef4cff9
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123.5 MB | Preview Download |
md5:256da9f05bce0e9327961a03ed6b3b51
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70.1 MB | Preview Download |
md5:4bdcaeef3c6f198a02282edae84d95ad
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66.1 MB | Preview Download |
md5:ef96b416164d228074869bb56ef96bd2
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44.7 MB | Preview Download |
md5:15c0443dcc5790d66b942ac97b91fc23
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74.3 MB | Preview Download |
md5:56694fad77c22ee12c68dc6d4d720a09
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91.8 MB | Preview Download |
md5:a72c31322575cd7b3de34399c18cb9dd
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46.9 MB | Preview Download |
md5:95d02751c0f0e990424abed06bf980a0
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55.4 MB | Preview Download |
md5:270eb879c1385af09b1346c3e4be6322
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35.8 MB | Preview Download |
md5:7abe7c4ff5bc25a2e705ab1e0a5df619
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63.2 MB | Preview Download |
md5:41221ceba9f9066d376ee9e4b7dcf35d
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67.0 MB | Preview Download |
md5:a76e1cf5d03005937d92979f231da410
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38.5 MB | Preview Download |
Additional details
Related works
- Is described by
- Preprint: arXiv:2301.04423 (arXiv)