UCF-WSI-Dataset
This is an open pathology image dataset for deep‑learning model development, containing 15 organ categories. The dataset follows FAIR principles and provides a large, diverse collection of whole‑slide pathology images for tasks such as disease classification, cancer and pneumonia cell segmentation, contributing to improved diagnostic and therapeutic strategies.
Dataset description and usage context
UCF-WSI-Dataset
Overview
This dataset contains whole‑slide histology images across 15 organ categories, intended for deep‑learning model development and validation. The dataset follows FAIR principles and provides a large‑scale, diverse, and richly annotated collection of whole‑slide tissue histology images, suitable for disease classification, cancer and pneumonia cell segmentation, and other medical imaging analysis tasks.
Dataset
The dataset can be accessed via the following link: UCF Necropsy WSI Dataset. The dataset includes 15 organ categories; example whole‑slide images for each category are shown below:
Code
- Code for running patch extraction can be found in the following Google Colab notebook: Patch_batch_processing.ipynb
- Code for running the classification task can be found in the following Google Colab notebook: UCF_WSI_Classification_model.ipynb
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