CAncer MEtastases in LYmph nOdes challeNge (CAMELYON) Dataset

Description

"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

License

CC0

Documentation

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6007545/

Managed By

Radboud University Medical Center

See all datasets managed by Radboud University Medical Center.

Contact

https://camelyon17.grand-challenge.org/

How to Cite

CAncer MEtastases in LYmph nOdes challeNge (CAMELYON) Dataset was accessed on DATE from https://registry.opendata.aws/camelyon.

Usage Examples

Tools & Applications

• ASAP Viewer by Geert Litjens
  
• CAMELYON Challenge by Diagnostic Image Analysis Group, Radboudumc, Nijmegen
  

Publications

• 1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset by Geert Litjens, et al.
  
• Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer by Babak Ehteshami Bejnordi, et al.
  
• From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge by Peter Bandi, et al.