Pathology Images of Scanners and Mobilephones (PLISM) Dataset
Version 2 2024-03-01, 19:59
Version 1 2023-08-07, 20:24
Posted on 2024-03-01 - 19:59 authored by Mieko Ochi
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.
- In PLISM-wsi, smartphone images were used as queries to create image groups for each staining condition corresponding to each tile image. The PLISM-wsi subset contains a total of 310,947 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.
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Ochi, Mieko; Komura, Daisuke; Onoyama, Takumi; Ishikawa, Shumpei (2023). Pathology Images of Scanners and Mobilephones (PLISM) Dataset. Figshare+. Collection. https://doi.org/10.25452/figshare.plus.c.6773925.v2
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FUNDING
AMED Practical Research for Innovative Cancer Control under grant number JP 23ck0106874
AMED Practical Research for Innovative Cancer Control under grant number JP 23ck0106640
Construction of a large-scale analysis platform for cancer histopathology using deep texture representation
Japan Society for the Promotion of Science
