Abstract The Artificial Bee Colony (ABC) technique is a highly effective method of
optimization inspired by the behavior of bees. Notably, the importance of the ABC algorithm …

Liver tumor segmentation from computed tomography (CT) images is a critical and
challenging task. Due to the fuzziness in the liver pixel range, the neighboring organs of the …

Optimization algorithms are necessary to solve many problems such as parameter tuning.
Particle Swarm Optimization (PSO) is one of these optimization algorithms. The aim of PSO …

This paper proposes an approach for liver segmentation in MRI images based on Whale
optimization algorithm (WOA). It is used to extract the different clusters in the abdominal …

Nature-inspired optimization has gained immense popularity over the past six decades and
has been extensively used across various disciplines. This paper aims to statistically …

Accurate liver segmentation is essential for radiation therapy planning of hepatocellular
carcinoma and absorbed dose calculation. However, liver segmentation is a challenging …

Nature, with its numerous surprising rules, serves as a rich source of creativity for the
development of artificial intelligence, inspiring researchers to create several nature-inspired …

Background: The most important aspect of medical image processing and analysis is image
segmentation. Fundamentally, the outcomes of segmentation have an impact on all …

Over the years, machine learning (ML) algorithms have proven their ability to make reliable
predictions of the toxicity of metal oxide nanoparticles. This paper proposed a predictive ML …

This paper proposes an approach for liver segmentation, depending on Antlion optimization
algorithm. It is used as a clustering technique to accomplish the segmentation process in …