The main goal of this work is to bring together Fuzzy Logic techniques and Biomedical images analysis, linking this two fields through an image segmentation problem approached by a Fuzzy c-Means algorithm. This work has two main cores. The first one is a formal structural analysis of some Fuzzy Logic concepts within the theory of Indistinguishabilitty Operators. The main actors of this part will be indistinguishability operators, sets of extensional fuzzy subsets, upper approximation operators and lower approximation operators. All these concepts will be explained in depth further in this work. The second core is a practical application of the Fuzzy c-Means algorithm to segmentate biomedical images of mammographies and bone marrow microscop...
Abstract: Fuzzy segmentation is an effective way of segmenting out objects in pictures containing bo...
Lack of information, imprecision, contradictory nature are common facts in medicine. Generally, the...
Image segmentation—the process of defining objects in im-ages—remains the most challenging problem i...
Currently, Mathematical Morphology (MM) has become a powerful tool in Digital Image Processing (DIP)...
The paper presents information theory based image segmentation algorithms. Both advantages and probl...
Medical imaging mainly manages and processes missing, ambiguous, omplementary, redundant and distor...
Currently, Mathematical Morphology (MM) has become a powerful tool in Digital Image Processing (DIP)...
This paper presents a robust fuzzy c-means (FCM) for an automatic effective segmentation of breast a...
AbstractFuzzy segmentation is a technique that assigns to each element in an image (which may have b...
Currently, Mathematical Morphology (MM) has become a powerful tool in Digital Image Processing (DIP)...
Currently, Mathematical Morphology (MM) has become a powerful tool in Digital Image Processing (DIP)...
Fuzzy segmentation is a technique that assigns to each element in an image (which may have been corr...
The objective of this research is to analyze the computation of medical image adaptive segmentation ...
International audienceIn this paper we discuss fuzzy techniques for the detection and analysis of po...
The objective of this research is to analyze the computation of medical image adaptive segmentation ...
Abstract: Fuzzy segmentation is an effective way of segmenting out objects in pictures containing bo...
Lack of information, imprecision, contradictory nature are common facts in medicine. Generally, the...
Image segmentation—the process of defining objects in im-ages—remains the most challenging problem i...
Currently, Mathematical Morphology (MM) has become a powerful tool in Digital Image Processing (DIP)...
The paper presents information theory based image segmentation algorithms. Both advantages and probl...
Medical imaging mainly manages and processes missing, ambiguous, omplementary, redundant and distor...
Currently, Mathematical Morphology (MM) has become a powerful tool in Digital Image Processing (DIP)...
This paper presents a robust fuzzy c-means (FCM) for an automatic effective segmentation of breast a...
AbstractFuzzy segmentation is a technique that assigns to each element in an image (which may have b...
Currently, Mathematical Morphology (MM) has become a powerful tool in Digital Image Processing (DIP)...
Currently, Mathematical Morphology (MM) has become a powerful tool in Digital Image Processing (DIP)...
Fuzzy segmentation is a technique that assigns to each element in an image (which may have been corr...
The objective of this research is to analyze the computation of medical image adaptive segmentation ...
International audienceIn this paper we discuss fuzzy techniques for the detection and analysis of po...
The objective of this research is to analyze the computation of medical image adaptive segmentation ...
Abstract: Fuzzy segmentation is an effective way of segmenting out objects in pictures containing bo...
Lack of information, imprecision, contradictory nature are common facts in medicine. Generally, the...
Image segmentation—the process of defining objects in im-ages—remains the most challenging problem i...