five

Pathology Images of Scanners and Mobilephones (PLISM) - Smartphone Images Dataset

收藏
Mendeley Data2024-01-31 更新2024-06-28 收录
下载链接:
https://plus.figshare.com/articles/dataset/Pathology_Images_of_Scanners_and_Mobilephones_PLISM_-_Smartphone_Images_Dataset/23590791
下载链接
链接失效反馈
官方服务:
资源简介:
The Pathology Images of Scanners and Mobilephones (PLISM) dataset was created for the evaluation of AI models’ robustness to domain shifts. PLISM is the first group-wised pathological image dataset that encompasses diverse tissue types stained under 13 H&E conditions, with multiple imaging media, including smartphones (7 scanners and 6 smartphones).In PLISM-sm, smartphone images were used as queries to create image groups for each staining condition corresponding to each tile image. The PLISM-sm subset contains a total of 57,902 images.Color and texture in digital pathology images are affected by H&E stain conditions (e.g. Harris or Carrazi) and digitalization devices (e.g. slide scanners or smartphones), which cause inter-institutional domain shifts.Please see the files 'stain_condition.png' and 'counterpart.png' for H&E staining conditions and devices used.This tar.gz file contains a collection of files labeled via the following file naming convention: (stain_name)/(device_name)/(top_left_x)_(top_left_y)_(right_lower_x)_(right_lower_y).pngThe csv file included with this dataset contains the following information:Tissue Type: The specific type of human tissue represented in the image, chosen from among 46 possible tissue types.Stain Type: The specific staining condition applied to the image, chosen from among 13 possible conditions.Device Type: The specific type of imaging device used to capture the image, chosen from among 13 possible device typesCoordinate: The xy coordinates of the top left and bottom right corners of each image (e.g., 1000_500_0_0)Image Path: The relative path to each image.See the whole slide images (WSIs) subset of the PLISM dataset in the Collection at https://doi.org/10.25452/figshare.plus.c.6773925
创建时间:
2024-01-31
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作