Application of the gradient descent for data balancing in diagnostic image analysis problems

The article proposes an algorithm for data balancing based on gradient descent. The proposed algorithm is able to partially mitigate the influence of the data imbalance problem which is commonly seen in the tasks of diagnostic image analysis. The authors have investigated the influence of the proposed algorithm on the accuracy of a fully convolutional neural network. The neural network was trained on unbalanced data as well as on the balanced by the algorithm. Recommendations on how to use the proposed algorithm are also formulated.