The brain is the largest and most complex structure in the central nervous system. It
dominates all activities in the body, and the lesions in the human body are also reflected in …

The goal of the segmentation of brain images is to separate the images in different non-
compatible homogenous areas reflecting the numerous anatomical structures. Brain …

In recent decades, region growing methods in image segmentation plays a vital role in
medical image processing. Nonetheless, the method needs more advancement to cope up …

The medical image processing has become indispensable with an increased demand for
systematic and efficient detection of brain tumor in a short period of time. There are various …

Computer aided diagnosis of liver tumors from abdominal Computer Tomography (CT)
images requires segmentation and analysis of tumor. Automatic segmentation of tumor from …

The medical image segmentation is the key approach of image processing for brain MRI
images. However, due to the visual complex appearance of image structures and the …

Image segmentation is one of vital researching branches in medical image processing and
analysis. Considering the characteristics of medical images, we propose a bi-directional …

The segmentation of images is considered a significant step in the processing of images.
Due to its simplicity and efficiency, Fuzzy c-means (FCM) is most commonly employed …

Fuzzy C-means (FCM) has been adopted to perform image segmentation due to its
simplicity and efficiency. Nevertheless it is sensitive to noise and other image artifacts …

Image segmentation is a crucial aspect of machine vision in which usable information is
collected from an input image. This relevant information might range from detecting …