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.
م.د. فاطمة حميد ،أ.م.د وفاء صباح محمد الخفاجي, International Journal of Psychosocial Rehabilitation,, 2020 - Cited by 1
This research develops a new method based on spectral indices and random forest classifier to detect paddy rice areas and then assess their distributions regarding to urban areas. The classification will be conducted on Landsat OLI images and Landsat OLI/Sentinel 1 SAR data. Consequently, developing a new spectral index by analyzing the relative importance of Landsat bands will be calculated by the random forest. The new spectral index has improved depending on the most three important bands, then two additional indices including the normalized difference vegetation index (NDVI), and standardized difference built-up index (NDBI) have been used to extract paddy rice fields from the data. Several experiments being
... Show MoreNeighShrink is an efficient image denoising algorithm based on the discrete wavelet
transform (DWT). Its disadvantage is to use a suboptimal universal threshold and identical
neighbouring window size in all wavelet subbands. Dengwen and Wengang proposed an
improved method, which can determine an optimal threshold and neighbouring window size
for every subband by the Stein’s unbiased risk estimate (SURE). Its denoising performance is
considerably superior to NeighShrink and also outperforms SURE-LET, which is an up-todate
denoising algorithm based on the SURE. In this paper different wavelet transform
families are used with this improved method, the results show that Haar wavelet has the
lowest performance among
Background: e cerebellum is divided into two hemispheres and contains a narrow midline zone called thevermis. A set of large folds are conventionally used to divide the overall structure into ten smaller "lobules". evermis receives fibres from the trunk and proximal portions of limbs, But the question is that does the cerebellum have the same measurementvalues in males and females of the same age?Material and method: e present study used 80 sectional brain MRI images (40: males, 40: females); 35-50 years old as indices of size for thevermian structures of the Cerebellum. is middle age group was taken because as known generally it could be neither an age of growth as inthe young nor of atrophy as in old individuals. e aim rega
... Show MoreThe last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of
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A simplified theoretical comparison of the hydrogen chloride (HCl) and hydrogen fluoride (HF) chemical lasers is presented by using computer program. The program is able to predict quantitative variations of the laser characteristics as a function of rotational and vibrational quantum number. Lasing is assumed to occur in a Fabry-Perot cavity on vibration-rotation transitions between two vibrational levels of hypothetical diatomic molecule. This study include a comprehensive parametric analysis that indicates that the large rotational constant of HF laser in comparison with HCl laser makes it relatively easy to satisfy the partial inversion criterion. The results of this computer program proved their credibility when compared with th
... Show MoreIn this work, the elemental constituents of smoker and nonsmoker
teeth samples of human were analyzed by Laser induced breakdown
spectroscopy method (LIBS). Many elements have been detected in
the healthy teeth samples, the important once are Ca, P, Mg, Fe, Pb
and Na. Many differences were found between (female and male)
teeth in Ca, P, Mg, Na and Pb contents. The concentrations of most
toxic elements were found significantly in the smoker group. The
maximum concentrations of toxic elements such as Pb, Cd and Co
were found in older male age above 60 year. Also, it was found that
the minimum concentrations of trace elements such as Ca, P and Na
exist in this age group. From these results it is clear that the
Recently, the internet has made the users able to transmit the digital media in the easiest manner. In spite of this facility of the internet, this may lead to several threats that are concerned with confidentiality of transferred media contents such as media authentication and integrity verification. For these reasons, data hiding methods and cryptography are used to protect the contents of digital media. In this paper, an enhanced method of image steganography combined with visual cryptography has been proposed. A secret logo (binary image) of size (128x128) is encrypted by applying (2 out 2 share) visual cryptography on it to generate two secret share. During the embedding process, a cover red, green, and blue (RGB) image of size (512
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Many approaches of different complexity already exist to edge detection in
color images. Nevertheless, the question remains of how different are the results
when employing computational costly techniques instead of simple ones. This
paper presents a comparative study on two approaches to color edge detection to
reduce noise in image. The approaches are based on the Sobel operator and the
Laplace operator. Furthermore, an efficient algorithm for implementing the two
operators is presented. The operators have been applied to real images. The results
are presented in this paper. It is shown that the quality of the results increases by
using second derivative operator (Laplace operator). And noise reduced in a good
The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv
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