OBJECTIVE: As there is no review paper on the research progress of the LB method, this
paper presents a review with an objective to give some thought regarding the different …

The science of solving clinical problems by analyzing images generated in clinical practice
is known as medical image analysis. The aim is to extract information in an affective and …

Pixel-wise image segmentation is a highly demanding task in medical-image analysis. In
practice, it is difficult to find annotated medical images with corresponding segmentation …

The process of segmenting tumor from MRI image of a brain is one of the highly focused
areas in the community of medical science as MRI is noninvasive imaging. This paper …

As fuzzy c-means clustering (FCM) algorithm is sensitive to noise, local spatial information is
often introduced to an objective function to improve the robustness of the FCM algorithm for …

A great number of improved fuzzy c-means (FCM) clustering algorithms have been widely
used for grayscale and color image segmentation. However, most of them are time …

Objective: Accurate diagnosis and prognosis are essential in lung cancer treatment
selection and planning. With the rapid advance of medical imaging technology, whole slide …

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 …

Diabetes or more precisely Diabetes Mellitus (DM) is a metabolic disorder happens because
of high blood sugar level in the body. Over the time, diabetes creates eye deficiency also …

Brain tumor segmentation consists of separating the different tumor tissues (solid or active
tumor, edema, and necrosis) from normal brain tissues: gray matter (GM), white matter (WM) …