Deep learning for medical image segmentation: State-of-the-art advancements and challenges

Image segmentation, a crucial process of dividing images into distinct parts or objects, has witnessed remarkable advancements with the emergence of deep learning (DL) techniques. The use of layers in deep neural networks, like object form recognition in higher layers and basic edge identification in lower layers, has markedly improved the quality and accuracy of image segmentation. Consequently, DL using picture segmentation has become commonplace, video analysis, facial recognition, etc. Grasping the applications, algorithms, current performance, and challenges are crucial for advancing DL-based medical image segmentation. However, there’s a lack of studies delving into the latest state-of-the-art developments in this field. Therefore, this survey aimed to thoroughly explore the most recent applications of DL-based medical image segmentation, encompassing an in-depth…