Deep learning (DL) has become widely used for medical image segmentation in recent
years. However, despite these advances, there are still problems for which DL-based …

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 …

As an emerging biomedical image processing technology, medical image segmentation has
made great contributions to sustainable medical care. Now it has become an important …

Deep learning-based image segmentation is by now firmly established as a robust tool in
image segmentation. It has been widely used to separate homogeneous areas as the first …

Deep learning (DL) algorithms have rapidly become a robust tool for analyzing medical
images. They have been used extensively for medical image segmentation as the first and …

Deep learning has been widely used for medical image segmentation and a large number of
papers has been presented recording the success of deep learning in the field. A …

In recent years, the segmentation of anatomical or pathological structures using deep
learning has experienced a widespread interest in medical image analysis. Remarkably …

Medical image segmentation is an important tool for current clinical applications. It is the
backbone of numerous clinical diagnosis methods, oncological treatments and computer …

Medical image segmentation plays a critical role in accurate diagnosis and treatment
planning, enabling precise analysis across a wide range of clinical tasks. This review begins …

Deep learning techniques have rapidly become important as a preferred method for
evaluating medical image segmentation. This survey analyses different contributions in the …