Image segmentation is one of the most important tasks in medical image analysis and is
often the first and the most critical step in many clinical applications. In brain MRI analysis …

Brain imaging techniques play an important role in determining the causes of brain cell
injury. Therefore, earlier diagnosis of these diseases can be led to give rise to bring huge …

Medical image segmentation has the priori guiding significance for clinical diagnosis and
treatment. In the past ten years, a large number of experimental facts have proved the great …

Purpose Delineation of thyroid nodule boundaries from ultrasound images plays an
important role in calculation of clinical indices and diagnosis of thyroid diseases. However, it …

Active contour model (ACM) has been a competitive tool in image segmentation because of
its desired segmentation result and accuracy. Nevertheless, it may become unstable while …

Thyroid nodule is one of the endocrine problem caused due to abnormal growth of cells.
This survival rate can be enhanced by earlier detection of nodules. Thus, the accurate …

Abstract Multiparametric Magnetic Resonance Imaging (MRI) is the most sensitive imaging
modality for breast cancer detection and is increasingly playing a key role in lesion …

We focused on fuzzy clustering in distributed environments. A novel distributed picture fuzzy
clustering method was presented. It combined the ideas of the facilitator model and picture …

Computed tomography (CT) imaging remains the most utilized modality for liver-related
cancer screening and treatment monitoring purposes. Liver, liver tumor and liver vasculature …

Thresholding is a direct and simple approach to extract different regions from an image. In its
basic formulation, thresholding searches for a global value that maximizes the separation …