In this paper, we present a novel algorithm for adap-tive fuzzy segmentation of MRI data and estimation of intensity inhomogeneities using fuzzy logic. MRI intensity inhomogeneities can be attributed to imperfections in the RF coils or some problems associated with the acquisition sequences. The result is a slowly-varying shading artifact over the image that can produce errors with conventional...

Pixel-wise spectral classiication is a widely used technique to produce thematic maps from remotely sensed multispectral imagery. It is commonly based on purely spectral features. In our approach we additionally consider additional spatial features in the form of local context information. After all, spatial context is the deening property of an image. Markov random eld modeling provides the as...

In this paper, we present a novel algorithm for adaptive fuzzy segmentation of MRI data and estimation of intensity inhomogeneities using fuzzy logic. MRI intensity inhomogeneities can be attributed to imperfections in the RF coils or some problems associated with the acquisition sequences. The result is a slowly-varying shading artifact over the image that can produce errors with conventional ...

A new method to clustering analysis, which is based on integration of graph theoretical method and fuzzy objective fimction algorithm, is developed. The connectivity mritriv derived from fuzzy limited neighborhood graph and the measurement for similarity and dissimilarity a re utilized to build a new fuzzy objective function that iinifles global data distribution and local spatial information. ...

The main purpose of this paper is to achieve improvement in the speed of Fuzzy Joint Points (FJP) algorithm. Since FJP approach is a basis for fuzzy neighborhood based clustering algorithms such as Noise-Robust FJP (NRFJP) and Fuzzy Neighborhood DBSCAN (FN-DBSCAN), improving FJP algorithm would an important achievement in terms of these FJP-based methods. Although FJP has many advantages such a...

in this paper, the notion of fuzzy semicompactness degrees isintroduced in $l$-fuzzy topological spaces by means of theimplication operation of $l$. characterizations of fuzzysemicompactness degrees in $l$-fuzzy topological spaces  areobtained, and some properties of fuzzy semicompactness degrees areresearched.