Medical image segmentation is a fundamental and challenging problem for analyzing
medical images. Among different existing medical image segmentation methods, graph …

In clinical settings, a lot of medical image datasets suffer from the imbalance problem which
hampers the detection of outliers (rare health care events), as most classification methods …

This is the first textbook of Virtual Anthropology, the new science that combines elements
from fields as diverse as anthropology, medicine, statistics, computing, scientific …

Image segmentation is often required as a preliminary and indispensable stage in the
computer aided medical image process, particularly during the clinical analysis of magnetic …

Medical image segmentation provides rich information in clinical applications for supporting
the advancement in the biomedical knowledge and to guide surgery. This paper reviews the …

Our previous works suggest that fractal texture feature is useful to detect pediatric brain
tumor in multimodal MRI. In this study, we systematically investigate efficacy of using several …

Breast cancer is one of the most commonly diagnosed cancer types among women.
Sonography has been regarded as an important imaging modality for diagnosis of breast …

This paper presents a systematic Type-II fuzzy expert system for diagnosing the human brain
tumors (Astrocytoma tumors) using T1-weighted Magnetic Resonance Images with contrast …

Image segmentation is a technique that partitioned the input image into prerequisite
semantic unique regions. Segmentation should stop as object of interest in an application is …

Accurate brain tissue segmentation in magnetic resonance imaging (MRI) has attracted the
attention of medical doctors and researchers since variations in tissue volume and shape …