The invention relates to noise tag based machine learning for anomaly assessment in medical imaging. For machine learning and application of a machine learning model for anomaly assessment in medical imaging, the machine learning uses lossy regularization, such as regularization used to train anomaly classification in chest radiography. The regularization may be noise and/or correlation regularization for noisy ground truth tags of the training data. Due to the fact that noise and/or correlation regularization are/is used in training, the machine learning model obtained according to the result can better classify anomalies in the medical image.
Noise tag based machine learning for anomaly assessment in medical imaging