Cancer-no cancer per image classification
2 papers with code • 1 benchmarks • 1 datasets
Binary classification between images with biopsy-proven cancers, and images without cancer. Only one image is used for the classification.
Benchmarks
These leaderboards are used to track progress in Cancer-no cancer per image classification
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CBIS-DDSM
Most implemented papers
Deep Learning to Improve Breast Cancer Early Detection on Screening Mammography
We also demonstrate that a whole image classifier trained using our end-to-end approach on the DDSM digitized film mammograms can be transferred to INbreast FFDM images using only a subset of the INbreast data for fine-tuning and without further reliance on the availability of lesion annotations.
Breast Cancer Diagnosis in Two-View Mammography Using End-to-End Trained EfficientNet-Based Convolutional Network
dpetrini/two-views-classifier
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IEEE Access 2022
To ensure statistical robustness, we test our system twice using: (a) 5-fold cross validation; and (b) the original training/test division of the dataset.
