Medical images are helpful for the diagnosis, treatment, and evaluation of diseases. Precise
medical image segmentation improves diagnosis and decision-making, aiding intelligent …

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

The health care sector is totally different from any other industry. It is a high priority sector
and consumers expect the highest level of care and services regardless of cost. The health …

In the recent decade, deep learning has taken lead over available analysis techniques.
Today's deep learning is used in diversified sectors like health care, traffic management …

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 …

Medical image segmentation is a vital task in medical imaging, aiming to extract meaningful
and precise information from images. While traditional methods have been extensively used …

Image segmentation is a branch of digital image processing which has numerous
applications in the field of analysis of images, augmented reality, machine vision, and many …

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

The performance of a Convolutional Neural Network (CNN) highly depends on its
architecture and corresponding parameters. Manually designing a CNN is a time-consuming …