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Identified edges of Hand X-ray medical image using ACO (left) and ACO with DnCNN (right) with operators: (a) Sin operator Equation (16), (b) KH operator Equation (17), (c) Chi operator Equation (18).
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Nowadays, demicontractive operators in terms of admissible perturbation are used to solve difficult tasks. The current research uses several demicontractive operators in order to enhance the quality of the edge detection results when using ant-based algorithms. Two new operators are introduced, χ -operator and K H -operator, the latter one is a Kra...
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Incorporating boundaries of the imaging object as a priori information to imaging algorithms can significantly improve the performance of electromagnetic medical imaging systems. To avoid overly complicating the system by using different sensors and the adverse effect of the subject's movement, a learning-based method is proposed to estimate the bo...
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... It is clearly from (iii) and (iv) that the demicontractive operator includes the directed operator. Demicontractive operators have many applications, for instance, demicontractive operators in terms of admissible perturbation are used during the construction phase of the matrix of ants artificial pheromone ( [29]). ...
... By (36), z n k − v n k ≤ z n k − T(z n ) + ν A (I − S)Az n k . It follows from (29) and (30) that lim k→∞ z n k − v n k = 0. This together with (37) implies that lim k→∞ u n k − z n k = 0 and u n k p † (k → ∞). ...
In this paper, the split fixed point and variational inclusion problem is considered. With the help of fixed point technique, Tseng-type splitting method and self-adaptive rule, an iterative algorithm is proposed for solving this split problem in which the involved operators S and T are demicontractive operators and g is plain monotone. Strong convergence theorem is proved under some mild conditions.
... Pintea and Ticala proposed the first related theoretical approach in [17]; a step forward was made in [18]. It includes more tests for both ant colony versions of medical image edge detection and a comparison of these techniques; details, including the efficiency of the new parameters and the use of some demicontractive operators, are presented. ...
... Demicontractive operators. As already stated in our previous work [18], a demicontractive operator (T) is defined by C, a subset of R (domains and co-domains). For an existing contraction coefficient (k < 1), each fixed point (p) of the demicontractive operator and all numbers (x ∈ C) the inequality ((1)) is true. ...
... For further details and examples, see [18,20,21]. ...
Nowadays, reliable medical diagnostics from computed tomography (CT) and X-rays can be obtained by using a large number of image edge detection methods. One technique with a high potential to improve the edge detection of images is ant colony optimization (ACO). In order to increase both the quality and the stability of image edge detection, a vector called pheromone sensitivity level, PSL, was used within ACO. Each ant in the algorithm has one assigned element from PSL, representing the ant’s sensibility to the artificial pheromone. A matrix of artificial pheromone with the edge information of the image is built during the process. Demi-contractions in terms of the mathematical admissible perturbation are also used in order to obtain feasible results. In order to enhance the edge results, post-processing with the DeNoise convolutional neural network (DnCNN) was performed. When compared with Canny edge detection and similar techniques, the sensitive ACO model was found to obtain overall better results for the tested medical images; it outperformed the Canny edge detector by 37.76%.
... In a recent paper [2], to enhance the quality of the edge detection results in medical image processing when using ant-based algorithms, the authors used as test functions admissible perturbations of some demicontractive operators. ...
... The class of demicontractive mappings, which includes, among others, the class of nonexpansive mappings having a fixed point and also the class of quasi-nonexpansive mappings, turned out to provide very convenient attenuation properties for medical images edge detection when using ant-based algorithms, as illustrated by the numerical tests reported by [2] and in Section 3 of the present paper. ...
... Our approach here is complementing the results reported in [2], where the authors studied the influence of choosing the appropriate parameter values for the quality of the edge detection algorithm. In the present paper, we focus on the process of selecting the test function used in building the heuristic. ...
The aim of this paper is to show analytically and empirically how ant-based algorithms for medical image edge detection can be enhanced by using an admissible perturbation of demicontractive operators. We thus complement the results reported in a recent paper by the second author and her collaborators, where they used admissible perturbations of demicontractive mappings as test functions. To illustrate this fact, we first consider some typical properties of demicontractive mappings and of their admissible perturbations and then present some appropriate numerical tests to illustrate the improvement brought by the admissible perturbations of demicontractive mappings when they are taken as test functions in ant-based algorithms for medical image edge detection. The edge detection process reported in our study considers both symmetric (Head CT and Brain CT) and asymmetric (Hand X-ray) medical images. The performance of the algorithm was tested visually with various images and empirically with evaluation of parameters.
Nowadays, swarm intelligence shows a high accuracy while solving difficult problems, including image processing problem. Image Edge detection is a complex optimization problem due to the high-resolution images involving large matrix of pixels. The current work describes several sensitive to the environment models involving swarm intelligence. The agents’ sensitivity is used in order to guide the swarm to obtain the best solution. Both theoretical general guidance and a practical example for a particular swarm are included. The quality of results is measured using several known measures.KeywordsSwarm intelligenceImage processingImage Edge Detection
