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CAncer MEtastases in LYmph nOdes challeNge (CAMELYON) Dataset

cancer computational pathology computer vision deep learning histopathology life sciences


"This dataset contains the all data for the CAncer MEtastases in LYmph nOdes challeNge or CAMELYON. CAMELYON was the first challenge using whole-slide images in computational pathology and aimed to help pathologists identify breast cancer metastases in sentinel lymph nodes. Lymph node metastases are extremely important to find, as they indicate that the cancer is no longer localized and systemic treatment might be warranted. Searching for these metastases in H&E-stained tissue is difficult and time-consuming and AI algorithms can play a role in helping make this faster and more accurate.

Update Frequency

As required




Managed By

Radboud University Medical Center

See all datasets managed by Radboud University Medical Center.


How to Cite

CAncer MEtastases in LYmph nOdes challeNge (CAMELYON) Dataset was accessed on DATE from

Usage Examples

Tools & Applications

Resources on AWS

  • Description
    Whole slide images with corresponding annotations including tumor, stroma and tumor infiltrating lymphocytes
    Resource type
    S3 Bucket
    Amazon Resource Name (ARN)
    AWS Region
    AWS CLI Access (No AWS account required)
    aws s3 ls --no-sign-request s3://camelyon-dataset/

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