A review on the recent segmentation and tumor grade classification techniques of brain
Magnetic Resonance (MR) Images is the objective of this paper. The requisite for early …

Computer-aided detection/diagnosis (CAD) systems can enhance the diagnostic capabilities
of physicians and reduce the time required for accurate diagnosis. The objective of this …

The study of brain disorders requires accurate tissue segmentation of magnetic resonance
(MR) brain images which is very important for detecting tumors, edema, and necrotic tissues …

In this paper, we propose a context-sensitive technique for unsupervised change detection
in multitemporal remote sensing images. The technique is based on fuzzy clustering …

Brain tumor is an abnormal growth of cells in the brain that its diagnosis in the early stages
can help us to prevent the dangers of the next stage. In this paper, a new meta-heuristic …

Hyperspectral imaging (HSI) is an emerging modality for various medical applications. Its
spectroscopic data might be able to be used to noninvasively detect cancer. Quantitative …

Medical informatics is the study that combines two medical data sources: biomedical record
and imaging data. Medical image data is formed by pixels that correspond to a part of a …

Medical image processing is one of the most famous image processing fields in this era.
This fame comes because of the big revolution in information technology that is used to …

Magnetic resonance imaging (MRI) has attracted considerable attention in medical
engineering community, since it is a non-invasive diagnostic technique and for its …

This study proposes a novel evolutionary kernel intuitionistic fuzzy c-means clustering
algorithm (EKIFCM) that combines Atanassov's intuitionistic fuzzy sets (IFSs) with kernel …