Background Artificial intelligence (AI) has become a prominent technique for medical
diagnosis and represents an essential role in detecting brain tumors. Although AI-based …

Over the last years, fractal and multifractal geometries were applied extensively in many
medical signal (1D, 2D or 3D) analysis applications like pattern recognition, texture analysis …

Background and Motivation: COVID-19 has resulted in a massive loss of life during the last
two years. The current imaging-based diagnostic methods for COVID-19 detection in …

The effectiveness of the treatment of breast cancer depends on its timely detection. An early
step in the diagnosis is the cytological examination of breast material obtained directly from …

Image segmentation is one of the most basic tasks in computer vision and remains an initial
step of many applications. In this paper, we focus on interactive image segmentation (IIS) …

Characterizing the performance of segmentation algorithms in brain images has been a
persistent challenge due to the complexity of neuroanatomical structures, the quality of …

The class of geometric deformable models, also known as level sets, has brought
tremendous impact to medical imagery due to its capability of topology preservation and fast …

Acute myelogenous leukemia (AML) is a subtype of acute leukemia, which is prevalent
among adults. The average age of a person with AML is 65 years. The need for automation …

We have developed and implemented methods of extracting morphological features from
images of biofilms in order to quantify the characteristics of the inherent heterogeneity. This …

Automatic segmentation of brain tumour is the process of separating abnormal tissues from
normal tissues, such as white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) …