The region and boundary characteristics of adhesive plant grain image are analyzed firstly in this paper. Then a method for judging the adhesion of grain is proposed by making use of image regional area threshold. Bas...
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The region and boundary characteristics of adhesive plant grain image are analyzed firstly in this paper. Then a method for judging the adhesion of grain is proposed by making use of image regional area threshold. Based on the analysis of various kinds of adhesion, a grain cluster segmentation algorithm for distinguishing split point of grain adhesion is put forward too, which makes full use of concavity-convexity of image boundary. Finally, the algorithm flow is presented in detail.
In order to reduce the massive manual intervention involved in the existing segmentation methods for human cross-section slice images, a segmentation algorithm based on the theory of region growing and threshold in no...
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ISBN:
(纸本)9781424447138
In order to reduce the massive manual intervention involved in the existing segmentation methods for human cross-section slice images, a segmentation algorithm based on the theory of region growing and threshold in normal gray histogram was proposed in this paper, according to the features of slice images of human brain. More exactly, these slice images were initially segmented coarsely by means of the region growing. Then the method of threshold in normal gray histogram was adopted to refine the segmentation. The experimental results indicate that the proposed algorithm can segment white matter accurately and effectively.
segmentation algorithms are well known in the field of image processing. In this work we propose an efficient and polynomial algorithm for image segmentation based on fuzzy set theory. The main difference with the cla...
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ISBN:
(纸本)9781424481262
segmentation algorithms are well known in the field of image processing. In this work we propose an efficient and polynomial algorithm for image segmentation based on fuzzy set theory. The main difference with the classical segmentation algorithms is in the output given by the segmentation process. Since the classical output for segmentation algorithms give us the homogeneous regions in the image, our proposal is to produce an hierarchical information (in a similar way as a dendrogam does in classical clustering methods) of how the groups are formed in the image, from the initial situation in which all pixels are in the same group to the final situation in which the whole image is divided in the minimal information units.
Array comparative genomic hybridization (aCGH) is a microarray technology that allows one to detect and map genomic alterations. The goal of aCGH analysis is to identify the boundaries of the regions where the number ...
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Array comparative genomic hybridization (aCGH) is a microarray technology that allows one to detect and map genomic alterations. The goal of aCGH analysis is to identify the boundaries of the regions where the number of DNA copies changes (breakpoint identification) and then to label each region as loss, neutral, or gain (calling). In this paper, we introduce a new algorithm, based on the shifting level model (SLM), with the aim of locating regions with different means of the log(2) ratio in genomic profiles obtained from aCGH data. We combine the SLM algorithm with the CGHcall calling procedure and compare their performances with 5 state-of-the-art methods. When dealing with synthetic data, our method outperforms the other 5 algorithms in detecting the change in the number of DNA copies in the most challenging situations. For real aCGH data, SLM is able to locate all the cytogenetically mapped aberrations giving a smaller number of false-positive breakpoints than the compared methods. The application of the SLM algorithm is not limited to aCGH data. Our approach can also be used for the analysis of several emerging experimental strategies such as high-resolution tiling array.
Hepatic vessel structure is very important to ensure the blood supply of the liver tissue. Therefore the knowledge of the hepatic vessel system is indispensable in liver surgery planning, for example before performing...
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ISBN:
(纸本)9781424441242
Hepatic vessel structure is very important to ensure the blood supply of the liver tissue. Therefore the knowledge of the hepatic vessel system is indispensable in liver surgery planning, for example before performing a liver resection. The purpose of this paper is to present an easy to use and fast method concerning hepatic vessel segmentation and risk analysis, which is intended to be applicable in clinical routine. Using CT scans vessels cannot be easily distinguished from other liver tissues. The segmentation algorithm used in this approach is mainly based on the arboreal structure of the hepatic vessel system. It is fully automatic and a prerequisite for the performance of a risk analysis concerning the minimal distances between tumors and vessels. A set of 20 oncological patient datasets was used to evaluate the segmentation algorithm and the risk analysis relating to their speed performance and ease of use, respectively. segmentation algorithm was always performed in less than 1 minute and risk analysis even in less than 10 seconds. Each step was performed fully automatical. The obtained results show, that both segmentation algorithm and risk analysis are easy to use because no user interaction is required. In combination with the speed performance it is possible for the surgeon to accomplish a preoperative and intraoperative liver surgery planning on his own, respectively.
The purpose was to evaluate a new semi-automated 3D region-growing segmentation algorithm for functional analysis of the left ventricle in multislice CT (MSCT) of the heart. Twenty patients underwent contrast-enhanced...
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The purpose was to evaluate a new semi-automated 3D region-growing segmentation algorithm for functional analysis of the left ventricle in multislice CT (MSCT) of the heart. Twenty patients underwent contrast-enhanced MSCT of the heart (collimation 16x0.75 mm;120 kV;550 mAseff). Multiphase image reconstructions with 1-mm axial slices and 8-mm short-axis slices were performed. Left ventricular volume measurements (end-diastolic volume, end-systolic volume, ejection fraction and stroke volume) from manually drawn endocardial contours in the short axis slices were compared to semi-automated region-growing segmentation of the left ventricle from the 1-mm axial slices. The post-processing-time for both methods was recorded. Applying the new region-growing algorithm in 13/20 patients (65%), proper segmentation of the left ventricle was feasible. In these patients, the signal-to-noise ratio was higher than in the remaining patients (3.2 +/- 1.0 vs. 2.6 +/- 0.6). Volume measurements of both segmentation algorithms showed an excellent correlation (all <= 0.0001);the limits of agreement for the ejection fraction were 2.3 +/- 8.3 ml. In the patients with proper segmentation the mean post-processing time using the region-growing algorithm was diminished by 44.2%. On the basis of a good contrast-enhanced data set, a left ventricular volume analysis using the new semi-automated region-growing segmentation algorithm is technically feasible, accurate and more time-effective.
We study the problem of decomposing a nonnegative matrix into a nonnegative combination of 0-1-matrices whose ones form a rectangle such that the sum of the coefficients is minimal. We present for the case of two rows...
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We study the problem of decomposing a nonnegative matrix into a nonnegative combination of 0-1-matrices whose ones form a rectangle such that the sum of the coefficients is minimal. We present for the case of two rows an easy algorithm that provides an optimal solution which is integral if the given matrix is integral. An additional integrality constraint makes the problem more difficult if the matrix has more than two rows. An algorithm that is based on the revised simplex method and uses only very few Gomory cuts yields exact integral solutions for integral matrices of reasonable size in a short time. For matrices of large dimension we propose a special greedy algorithm that provides sufficiently good results in numerical experiments. (C) 2008 Elsevier B.V. All rights reserved.
Thesis studied correlations between swallowing accelerometry parameters and anthropometrics in 50 healthy participants. Anthropometrics include: age, gender, weight, height, body fat percent, neck circumference and ma...
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Thesis studied correlations between swallowing accelerometry parameters and anthropometrics in 50 healthy participants. Anthropometrics include: age, gender, weight, height, body fat percent, neck circumference and mandibular length. Dual-axis swallowing signals, from a biaxial accelerometer were obtained for 5-saliva and 10-water (5-wet and 5-wet chin-tuck) swallows per participant. Two patient-independent automatic segmentation algorithms using discrete wavelet transforms of swallowing sequences segmented: 1) saliva/wet swallows and 2) wet chin-tuck swallows. Extraction of swallows hinged on dynamic thresholding based on signal *** correlation analysis was performed on sets of anthropometric and swallowing signal variables including: variance, skewness, kurtosis, autocorrelation decay time, energy, scale and peak-amplitude. For wet swallows, significant linear relationships were found between signal and anthropometric variables. In superior-inferior directions, correlations linked weight, age and gender to skewness and signal-memory. In anterior-posterior directions, age was correlated with kurtosis and signal-memory. No significant relationship was observed for dry and wet chin-tuck swallowing
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