All rights reserved. Hae-Yeoun, L. Codella, et al. An automatic left ventricle LV segmentation algorithm is presented for quantification of cardiac output and myocardial mass in clinical practice.
The LV endocardium is first segmented using region growth with iterative thresholding by detecting the effusion into the surrounding myocardium and tissues. Then the epicardium is extracted using the active contour model guided by the endocardial border and the myocardial signal information estimated by iterative thresholding.
The ITHACA algorithm agreed well with manual tracing with a mean difference of blood volume and myocardial mass being 2. The difference was smaller than the difference between manual tracing and the MASS software approximately These experimental results support that the proposed ITHACA segmentation is accurate and useful for clinical practice.
Hammouche, K. Diaf, et al. The multilevel thresholding problem is often treated as a problem of optimization of an objective function. This paper presents both adaptation and comparison of six meta-heuristic techniques to solve the multilevel thresholding problem: a genetic algorithm, particle swarm optimization, differential evolution, ant colony, simulated annealing and tabu search. Experiments results show that the genetic algorithm, the particle swarm optimization and the differential evolution are much better in terms of precision, robustness and time convergence than the ant colony, simulated annealing and tabu search.
Among the first three algorithms, the differential evolution is the most efficient with respect to the quality of the solution and the particle swarm optimization converges the most quickly.
Horng, M. Image thresholding is an important technique for image processing and pattern recognition. Many thresholding techniques have been proposed in the literature. Among them, the maximum entropy thresholding MET has been widely applied. The experimental results manifest that the proposed MEHBMOT algorithm can search for multiple thresholds which are very close to the optimal ones examined by the exhaustive search method.
In comparison with the other three thresholding methods, the segmentation results using the MEHBMOT algorithm is the best and its computation time is relatively low. Among them, the minimum cross entropy thresholding MCET has been widely applied.
Three different methods included the exhaustive search, the particle swarm optimization PSO and the quantum particle swarm optimization QPSO methods are also implemented for comparison with the results of the proposed method. The experimental results manifest that the proposed HBMO-based MCET algorithm can efficiently search for multiple thresholds which are very close to the optimal ones examined by the exhaustive search method. Acharya, G. Kittler, J. Illingworth A computationally efficient solution to the problem of minimum error thresholding is derived under the assumption of object and pixel grey level values being normally distributed.
The method is applicable in multithreshold selection. This paper describes a novel approach to binarization techniques. It presents a way of obtaining a threshold that depends both on the image and the final application using a semantic description of the histogram and a neural network. The intended applications of this technique are high precision OCR algorithms over a limited number of document types. The input image histogram is smoothed and its derivative is found.
Using a polygonal version of the derivative and the smoothed histogram, a new description of the histogram is calculated. Using this description and a training set, a general neural network is capable of obtaining an optimum threshold for our application.
Liou, R. Horng, et al. Multi-level thresholding selection by using the honey bee mating optimization, Shenyang. In this paper, a new multilevel image thresholding algorithm based on the technology of the honey bee mating optimization HBMO is proposed.
The experimental results reveal two important interested results for other three image thresholding methods. One is that the results of PSO and Fast Ostu's method are unstable that extraordinary segmentations are generated.
Otsu, N. Pai, Y. Chang, et al. Document image binarization involves converting gray level images into binary images, which is a feature that has significantly impacted many portable devices in recent years, including PDAs and mobile camera phones. Given the limited memory space and the computational power of portable devices, reducing the computational complexity of an embedded system is of priority concern. This work presents an efficient document image binarization algorithm with low computational complexity and high performance.
Login Join User. Solution Manual. Medicine of a disease or process not accompanied by readily discernible signs or symptoms. Astronomy of a celestial body conceal an apparently smaller body from view by passing or being in front of it. The word occult comes from the Latin occultus clandestine, hidden, secret , referring to "knowledge of the hidden".
In the medical sense it is used commonly to refer to a structure or process that is hidden, e.
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