In the computer vision domain, image segmentation is one of the most challenging and
prominent concepts. For segmentation, image pixels are categorized based on similar …

Background: Medical image segmentation has an essential role in computer-aided
diagnosis systems in different applications. The study has mainly focused on some few …

Medical image segmentation has greatly increased healthcare sustainability. It is currently a
major research area in the field of computer vision. The many artefacts inherent in medical …

In recent days, deep learning is on rage and is gaining a huge amount of popularity due to
its supremacy in terms of accuracy. Deep learning is being used for a vast number of …

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

One of the most important areas in medical image analysis is segmentation, in which raw
image data is partitioned into structured and meaningful regions to gain further insights. By …

Accurate delineation of medical images is crucial for computer-aided diagnosis and
treatment. However, the current clinical practice primarily relies on segmentation produced …

Images are divided into a sequence of non-overlapping sections during image
segmentation. These areas give human tissues completely dissimilar structures and put the …

During the last few years, medical image segmentation using deep learning has become the
most active research area in computer vision. Effectively, researchers become more and …

Cardiac image segmentation has great significance of making correct diagnoses of cardiac
diseases, and providing useful information for clinical treatment and surgery. Among cardiac …