Deep Learning, Artificial Intelligence, Medical Imaging, Image Classification, Biomedical Segmentation.
achieves 42%. Finally, Zhang et al. (2020) obtain a 75% Dice to proposed one 41%. Authors argue that the large performance gap is due to over-engineering to the specific dataset. Also, authors only use small network and do not perform specific fine-tuning. By making use of classification labels,