Simple Summary Automatic segmentation of organs and other regions of interest is a
promising approach for reducing the workload of doctors in radiotherapeutic planning, but it …

Cancer is becoming the most toxic ailment identified among individuals worldwide. The
mortality rate has been increasing rapidly every year, which causes progression in the …

Medical image segmentation plays an important role in medical diagnosis, and has received
extensive attention in recent years. A large number of convolutional neural network based …

This study investigates the potential of eye-tracking technology and the Segment Anything
Model (SAM) to design a collaborative human-computer interaction system that automates …

Nuclei identification is a fundamental task in many areas of biomedical image analysis
related to computational pathology applications. Nowadays, deep learning is the primary …

Liver segmentation is a crucial step in surgical planning from computed tomography scans.
The possibility to obtain a precise delineation of the liver boundaries with the exploitation of …

Antifreeze proteins (AFPs) are found in different living organisms like plants, insects, and
fish. AFPs avoid the formation of ice crystals in these organisms and make them able to …

Active contour models (ACMs) are popular and widely used for many image segmentation
applications and obtain promising results. However, these methods are unable to achieve …

In recent years, a constant and fast information growing has characterized digital
applications in the majority of real-life scenarios. Thus, a new information asset, namely Big …

Over the last decade, artificial intelligence (AI) has made an enormous impact on a wide
range of fields, including science, engineering, informatics, finance, and transportation. In …