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DBTex Lesion Detection Challenge Predictions
The DBTex lesion detection challenge tasked participating teams with detecting lesions in the BCS-DBT test set. The challenge had two phases: DBTex1 and and DBTex2. Here we we provide the BCS-DBT lesion predictions made by all participating teams for both phases, for both the BCS-DBT test and validation sets, as “team“team_predictions_bothphases.zip”zip”. Please see see here under under “Output format for the DBTex2 Challenge test set results” for a description of how these results are formatted. Finally, when comparing lesion bounding box predictions to the image data, be sure to load the images correctly according to the above “Required Preprocessing of DBT Images”.
If you use these predictions, please reference the DBTex challenge paper:
Konz N, Buda M, Gu H, et al. A Competition, Benchmark, Code, and Data for Using Artificial Intelligence to Detect Lesions in Digital Breast Tomosynthesis. JAMA Netw Open. 2023;6(2):e230524. doi:10.1001/jamanetworkopen.2023.0524
Acknowledgements
We would like to acknowledge the individuals and institutions that have provided data for this collection:
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