The segmentation of the retinal vascular tree presents a major step for detecting ocular
pathologies. The clinical context expects higher segmentation performance with a reduced …

Today numerous imaging systems are utilized in medical treatment. There are a variety of
imaging techniques for the diagnosis of brain tumors, lung nodules and liver tumors and …

Efficient big data clustering is a requirement for massive data generating in this digitalized
connected world. The traditional clustering algorithms do not scale over massively sized and …

Different respiratory infections cause abnormal symptoms in lung parenchyma that show in
chest computed tomography. Since December 2019, the SARS-COV-2 virus, which is the …

With recent advanced technologies, various automated diagnosis tools were developed to
prevent retinal diseases. The automatic segmentation of blood vessels can help detect …

The clustering of big data is a challenging task. The traditional clustering algorithms are
inefficient for clustering big data. The recent researches in this field suggest that the …

Fuzzy C‐Means (FCM) is a widely used clustering algorithm that performs well in various
scientific applications. Implementing FCM involves a massive number of computations, and …

Retinal blood vessels structure analysis is an important step in the detection of ocular
diseases such as diabetic retinopathy and retinopathy of prematurity. Accurate tracking and …

The presence of a normal large blood vessel (LBV) in a tumor region can impact the
evaluation of quantitative dynamic contrast‐enhanced magnetic resonance imaging (DCE …

Underwater image segmentation is useful for benthic habitat mapping and monitoring;
however, manual annotation is time-consuming and tedious. We propose automated …