构建乳腺癌病理图像核分割数据集NuSeC，支持未来方法对比研究。
NuSeC: A Dataset for Nuclei Segmentation in Breast Cancer Histopathology Images
- 从25名患者每例选4张1024×1024图像，共100张构成数据集。
- 训练集75张含约3万核，测试集25张含约6千核，按患者划分避免泄露。
- 专为核分割方法对比设计，适合病理图像分析研究者使用。
NuSeC数据集从25名患者的切片中，每例选取4张1024×1024像素的图像，共计100张。为确保未来研究方法的可比性，将数据集按患者划分：随机从每例4张图中选1张作为测试集，剩余3张用于训练。训练集包含75张图像，约30,000个核结构；测试集包含25张图像，约6,000个核结构。该划分方式避免了患者间数据泄露，保障评估可靠性。
原文摘要 · Abstract (English)
The NuSeC dataset is created by selecting 4 images with the size of 1024*1024 pixels from the slides of each patient among 25 patients. Therefore, there are a total of 100 images in the NuSeC dataset. To carry out a consistent comparative analysis between the methods that will be developed using the NuSeC dataset by the researchers in the future, we divide the NuSeC dataset 75% as the training set and 25% as the testing set. In detail, an image is randomly selected from 4 images of each patient among 25 patients to build the testing set, and then the remaining images are reserved for the training set. While the training set includes 75 images with around 30000 nuclei structures, the testing set includes 25 images with around 6000 nuclei structures.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。