Evaluation of how to apply deep learning in biomedical engineering

Recent developments in image processing have contributed to the advancement of rapidly developing technological systems. Studies on image processing, especially in the health field, have increased its popularity. Despite the success achieved on existing methods, whether it is medical images or images in other fields; the deep learning model is a model that contributes more in terms of time and performance compared to existing methods. While processing is done on single-layer images with existing methods, high-performance results can be obtained on multi-layer images with the deep learning model. The most important feature of deep learning is that it processes the operations on the image in a single go and can discover parameters that need to be entered manually. In addition, the fact that technology companies are turning to deep learning has increased their competitive power among themselves, and the methods they have built on deep learning in scientific terms have started to be preferred more than existing methods. In the biomedical field, which is one of the areas with limited dataset access, datasets have recently been obtained rapidly.