ISIC2018_Task1-2_Training_Input.zip
收藏DataCite Commons2023-04-26 更新2024-08-18 收录
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https://figshare.com/articles/dataset/ISIC2018_Task1-2_Training_Input_zip/22698379
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资源简介:
To comply with the attribution requirements of the CC-BY-NC license , the aggregate "ISIC 2018: Training" data must be cited as: HAM10000 Dataset: (c) by ViDIR Group, Department of Dermatology, Medical University of Vienna; https://doi.org/10.1038/sdata.2018.161<br> MSK Dataset: (c) Anonymous; https://arxiv.org/abs/1710.05006; https://arxiv.org/abs/1902.03368 When referencing this dataset in your own manuscripts and publications, please use the following full citations: [1] Noel Codella, Veronica Rotemberg, Philipp Tschandl, M. Emre Celebi, Stephen Dusza, David Gutman, Brian Helba, Aadi Kalloo, Konstantinos Liopyris, Michael Marchetti, Harald Kittler, Allan Halpern: "Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)", 2018; https://arxiv.org/abs/1902.03368<br> [2] Tschandl, P., Rosendahl, C. & Kittler, H. The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions. Sci. Data 5, 180161 doi:10.1038/sdata.2018.161 (2018).
为遵守CC-BY-NC(知识共享署名-非商业性使用)许可的署名要求,聚合后的ISIC 2018:训练数据集必须按如下方式引用:
HAM10000数据集:(版权归维也纳医科大学皮肤科ViDIR团队所有;https://doi.org/10.1038/sdata.2018.161)
MSK数据集:(版权归匿名作者所有;https://arxiv.org/abs/1710.05006;https://arxiv.org/abs/1902.03368)
若您在自主投稿的手稿或学术出版物中引用该数据集,请使用以下完整参考文献:
[1] Noel Codella、Veronica Rotemberg、Philipp Tschandl、M. Emre Celebi、Stephen Dusza、David Gutman、Brian Helba、Aadi Kalloo、Konstantinos Liopyris、Michael Marchetti、Harald Kittler、Allan Halpern:《面向黑色素瘤检测的皮肤病变分析2018:由国际皮肤影像协作组(International Skin Imaging Collaboration,ISIC)主办的挑战赛》,2018;https://arxiv.org/abs/1902.03368
[2] Tschandl, P., Rosendahl, C. & Kittler, H. 《HAM10000数据集:多源常见色素性皮肤病变皮肤镜图像大型集合》. Sci. Data 5, 180161 doi:10.1038/sdata.2018.161 (2018).
提供机构:
figshare
创建时间:
2023-04-26
搜集汇总
数据集介绍

背景与挑战
背景概述
该数据集是ISIC 2018挑战赛的训练输入数据,包含大量多源皮肤镜图像,用于皮肤病变分析和黑色素瘤检测研究。数据集由多个研究机构合作提供,遵循CC-BY-NC许可,需在引用时注明来源。
以上内容由遇见数据集搜集并总结生成



