Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is efficient, has very few free parameters to tune, and the authors show how to tune the few remaining parameters. Results show that the method reliably aligns various datasets including two facial datasets and two medical datasets of prostate and brain MRI images and demonstrates efficiency in terms of performance and a reduction of the computational cost.
Colorectal cancer CRC is the third most commonly diagnosed cancer in males and the second in female, so it is a common and life-threatening disease serum of 48 males and 40 females suffering from CRC disease as group one (G1) without taking a chemotherapy dose, the same patients group tow (G2) after taking the first chemotherapy dose, while group three (G3) whose patients in (G1) and (G2) after second taking a chemotherapy dose. and group four (G4) consist of (30 males and 30 females) healthy Iraqi control. Results showed a significant increase in IL-17, IL-17RA and CEA in G1, while there was a significant decrease in vitamin D concentration in G1 than other groups, also there was positive (+ ve) significant correlation between IL-17 and CE
... Show MoreBackground: Saliva is one of the most important etiological host factors in relation to dental caries. It affects the carious process by its organic and inorganic constituents; in addition to its physiological functions as (flow rate, pH and buffer capacity). The aims of this study were to determine the concentrations of major elements (calcium and phosphorus) and trace elements (ferrous iron, nickel, chromium and aluminum) in saliva among a group of adolescent girls, and to explore the relation of these elements, flow rate and pH with dental caries. Material & Methods: The study group consisted of 25 girls with an age of 13-15 years old. Dental caries was diagnosed by both clinical and radiographical examinations following the criteria of
... Show MoreEstimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling the Symmetric gray scale texture image and estimating by using
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Aspect categorisation and its utmost importance in the eld of Aspectbased Sentiment Analysis (ABSA) has encouraged researchers to improve topic model performance for modelling the aspects into categories. In general, a majority of its current methods implement parametric models requiring a pre-determined number of topics beforehand. However, this is not e ciently undertaken with unannotated text data as they lack any class label. Therefore, the current work presented a novel non-parametric model drawing a number of topics based on the semantic association present between opinion-targets (i.e., aspects) and their respective expressed sentiments. The model incorporated the Semantic Association Rules (SAR) into the Hierarchical Dirichlet Proce
... Show MoreBackground :Atherosclerosis is the most
frequent underlying cause of ischemic heart
disease and a major cause of death all over the
world. This study was carried out to analyze and
compare the angiographic findings in patients
with diabetes mellitus versus non diabetics with
coronary heart disease , and to correlate these
findings with some risk factors for coronary
heart disease.
Methods: A total of 100 patients were studied,
50 with diabetes mellitus, and 50 non diabetics.
This study was carried out at Al-Sadr teaching
hospital in Basrah, Southern Iraq during the
period April 2009- September 2009. All patients
were known to have coronary heart disease. Risk
factors for coronary heart disease
The basic analytical formula for particle-hole state densities is derived based on the non-Equidistant Spacing Model (non-ESM) for the single-particle level density (s.p.l.d.) dependence on particle excitation energy u. Two methods are illustrated in this work, the first depends on Taylor series expansion of the s.p.l.d. about u, while the second uses direct analytical derivation of the state density formula. This treatment is applied for a system composing from one kind of fermions and for uncorrected physical system. The important corrections due to Pauli blocking was added to the present formula. Analytical comparisons with the standard formulae for ESM are made and it is shown that the solution reduces to earlier formulae providing m
... Show MoreProblem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
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Background: Periodontal diseases are inflammatory diseases affecting the supporting tissues of the teeth. One of the leading environmental factors that are closely related not only to the risk but also to the prognosis of periodontitis is smoking. This study aimed to evaluate the influence of smoking on periodontal health status and to measure the levels of matrix metalloproteinase-9 in smokers and nonsmokers chronic periodontitis patients, also it aimed to test the correlation between the levels of matrix metalloproteinase-9 and the clinical periodontal parameters. Materials and Methods: Five milliliters samples of un-stimulated whole saliva and full-mouth clinical periodontal recordings (plaque index, gingival index, bleeding on probing,
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Schiff base ligand (H2CANPT) was prepared by two steps: first, by the condensation of curcumin with 4-amino antipyrin produces4,4'-(((1E,3Z,5Z,6E)-1,7-bis(4-hydroxy-3- methoxyphenyl)hepta-1,6-diene-3,5-diylidene)bis(azanylylidene))bis(1,5-dimethyl-2-phenyl- 1,2-dihydro-3H-pyrazol-3-one) (CANP). Second, by the condensation of (CANP) with L-tyrosine produces2,2'-(((3Z,3'Z)-(((1E,3Z,5Z,6E)-1,7-bis(4-hydroxy-3-methoxyphenyl)hepta 1,6-diene-3,5-diylidene)bis(azanylylidene))bis(1,5-dimethyl-2-phenyl-1,2-dihydro-3-H-pyrazole- 4-yl-3-ylidene))bis(azanylylidene))bis(3-(4-hydroxyphenyl)propanoic acid) (H2CANPT). The resulted Schiff comported as hexadentate coordinated with (N4O2) atoms, then it was treated with some transition and non-transaction met
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