Genetic Algorithm-Based Anisotropic Diffusion Filter and Clustering Algorithms for Thyroid Tumor Detection

Abstract

Medical imaging is a technique that has been used for diagnosis and treatment of a large number of diseases. Therefore it has become necessary to conduct a good image processing to extract the finest desired result and information. In this study, genetic algorithm (GA)-based clustering technique (K-means and Fuzzy C Means (FCM)) were used to segment thyroid Computed Tomography (CT) images to an extraction thyroid tumor. Traditional GA, K-means and FCM algorithms were applied separately on the original images and on the enhanced image with Anisotropic Diffusion Filter (ADF). The resulting cluster centers from K-means and FCM were used as the initial population in GA for the implementation of GAK-Mean and GAFCM. Jaccard index was used to study resemblance, dissimilarity, distance between two sets of images, and effect of ADF on enhancing the CT images. The results showed that ADF increases the segmentation accuracy, where the value of Jaccard index of similarity between the ground truth image and segmented image was increased for all segmentation algorithms, in particular for FCM and GAFCM where similarity percent was up to 88%.

Using Non-dominated Sorting Particle Swarm Optimization Algorithm II for Bi-objective Flow Shop Scheduling Problems

“…The scheduling of the replacement flow shop can be described as [8]: n workpieces are to be processed on m machines. The processing sequence of each workpiece is the same, the sequence of workpieces processed by each machine is also the same, and the processing time of each workpiece on each machine.…”

“…Scheduling objectives generally includes: minimizing the maximum workpiece delay; minimizing the total workpiece flow time (TFT); maximizing the completion time of all workpieces (Makespan) being the shortest; average workpiece waiting time being the shortest, etc. [8]. In this paper, maximum completion time and total flow time are the shortest of the two goals.…”

“…Furthermore, Abbas. [ 8] proposed a type of virtual multi-objective annealing algorithm, which generates a set of random weight vectors to construct a set of evaluation functions and then performs a local search based on each evaluation function under the guidance of a simulated annealing strategy.…”

Enhancing Fuzzy C-Means Clustering with a Novel Standard Deviation Weighted Distance Measure

“…The present study focused on the examination of water samples collected from the Nile River, with a specific emphasis on the drinking water stations (CDWPs) situated in Cairo 6 . The study addresses the problem of medical imaging of cancer diseases by applying genetic algorithms and hazy and acute cluster algorithms using an ADF diffusion filter that improved the accuracy of the algorithms' results 7 . This study presented a data clustering technique using the modified Voronoi Fuzzy Algorithm (VFCA), which aims to divide the sensed area into a number of cells that were grouped using the Fuzzy C Mean Clustering (FCM) algorithm.…”

Study the Quality of IMRT and VMAT Treatment Planning Techniques (TPS) Using Indices of Achievement (IOA) Nasopharyngeal Cancer Plans

“…Compared to other IMRT delivery methods, VMAT may lower both the monitor unit and the total dose. This can help lower the risk of some side effects or the development of a second cancer (the sliding window approach and those not based on direct aperture optimization [22,23]). While VMAT (or IMRT) is the current gold standard, a 2016 ESTRO study of centers in 24 European nations found that over 30 percent of those surveyed reported using 3-dimensional conformal radiation (3DCRT) on the head and neck [24,25].…”