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

dataset
posted on 2024-03-01, 19:56 authored by Mieko OchiMieko Ochi, Daisuke KomuraDaisuke Komura, Shumpei Ishikawa, Takumi Onoyama

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).png
  • The csv file included with this dataset contains the following information:
  1. Tissue Type: The specific type of human tissue represented in the image, chosen from among 46 possible tissue types.
  2. Stain Type: The specific staining condition applied to the image, chosen from among 13 possible conditions.
  3. Device Type: The specific type of imaging device used to capture the image, chosen from among 13 possible device types
  4. Coordinate: The xy coordinates of the top left and bottom right corners of each image (e.g., 1000_500_0_0)
  5. 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

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

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History

Research Institution(s)

Department of Preventive Medicine, Graduate School of Medicine, The University of Tokyo

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Competing Interest Statement

We have no financial relationships.

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