Abstract
Abstract In this paper we introduce the concept of segmentation based on mathematical approach using graph theory algorithms using the family of augmenting paths algorithms. We present a new program, an implementation, algorithms and obtained results devoted to segmentation of biomedical data. We implement our program for handling with segmentation, counting a measure of the existence of the minerals in the biomedical data. As a consequence we prove the existence of minerals in the data obtained from the brain of rabbits.
Highlights
This paper is motivated by the problem of segmentation and its application on real biomedical data
In this paper we introduce the concept of segmentation based on mathematical approach using graph theory algorithms using the family of augmenting paths algorithms
We present a new program, an implementation, algorithms and obtained results devoted to segmentation of biomedical data
Summary
This paper is motivated by the problem of segmentation and its application on real biomedical data. We focused on a graph theoretical approach to segmentation which is called "graph cutting" [2, 4, 13,14,15,16]. It means that we have data represented as an image. According to [2,3,4, 13] the minimal cut in network is the equivalent problem to finding a segmentation. We present different segmentation techniques used in image processing and we focus on graph theory based methods. The last Section No 5 is devoted to the conclusion and the summary
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