Noor Mualla¹, Essam H Houssein^{2, *}, M. R. Hassan¹

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 591-605, 2020, DOI:10.32604/cmc.2020.08580

Abstract Chronological age estimation using panoramic dental X-ray images is an essential task in forensic sciences. Various statistical approaches have proposed by considering the teeth and mandible. However, building automated dental age estimation based on machine learning techniques needs more research efforts. In this paper, an automated dental age estimation is proposed using transfer learning. In the proposed approach, features are extracted using two deep neural networks namely, AlexNet and ResNet. Several classifiers are proposed to perform the classification task including decision tree, k-nearest neighbor, linear discriminant, and support vector machine. The proposed approach is evaluated using a number of suitable… More >

Satya Prakash Yadav^{1, *}, Sachin Yadav²

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 303-321, 2020, DOI:10.32604/cmes.2020.08459

Abstract This paper presents a low intricate, profoundly energy effective MRI Images combination intended for remote visual sensor frameworks which leads to improved understanding and implementation of treatment; especially for radiology. This is done by combining the original picture which leads to a significant reduction in the computation time and frequency. The proposed technique conquers the calculation and energy impediment of low power tools and is examined as far as picture quality and energy is concerned. Reenactments are performed utilizing MATLAB 2018a, to quantify the resultant vitality investment funds and the reproduction results show that the proposed calculation is very quick… More >

Jinwei Wang^{1, *}, Yang Zhang¹

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 99-112, 2020, DOI:10.32604/cmc.2020.04373

Abstract In the paper, a convolutional neural network based on quaternion transformation is proposed to detect median filtering for color images. Compared with conventional convolutional neural network, color images can be processed in a holistic manner in the proposed scheme, which makes full use of the correlation between RGB channels. And due to the use of convolutional neural network, it can effectively avoid the one-sidedness of artificial features. Experimental results have shown the scheme’s improvement over the state-of-the-art scheme on the accuracy of color image median filtering detection. More >

Sevan Goenezen^1,*, Ping Luo¹, Baik Jin Kim¹, Maulik Kotecha¹, Yue Mei^2,3

Molecular & Cellular Biomechanics, Vol.16, Suppl.2, pp. 46-48, 2019, DOI:10.32604/mcb.2019.07348

Abstract It is well known that the mechanical properties of tissues may vary spatially due to changing tissue types or due to inherent tissue disease. For example, the biomechanical properties are known to vary throughout blood vessels [1]. Diseases such as cancers may also lead to locally altered mechanical properties, thus allow a preliminary diagnosis via finger palpation. Quantifying the mechanical property distribution of tissues for a given constitutive equation will allow to characterize the biomechanical response of tissues. This may help to 1) predict disease progression, 2) diagnose diseases that alter the biomechanics of the tissue, e.g., skin cancers, breast… More >

Xiaoya Guo¹, Dalin Tang^1,2,*, David Molony³, Chun Yang², Habib Samady³, Jie Zheng⁴, Gary S. Mintz⁵, Akiko Maehara⁵, Jian Zhu⁶, Genshan Ma⁶, Mitsuaki Matsumura⁵, Don P. Giddens^3,7

Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 75-76, 2019, DOI:10.32604/mcb.2019.05743

Abstract Atherosclerotic plaque progression is generally considered to be closely associated with morphological and mechanical factors. Plaque morphological information on intravascular ultrasound (IVUS) and optical coherence tomography (OCT) images could complement each other and provide for more accurate plaque morphology. Fluid-structure interaction (FSI) models combining IVUS and OCT were constructed to obtain accurate plaque stress/strain and flow shear stress data for analysis. Accuracy and completeness of imaging and advanced modeling lead to accurate plaque progression predictions.
In vivo IVUS and OCT coronary plaque data at baseline and follow-up were acquired from left circumflex coronary and right coronary artery of one… More >

Jing Liu^1,5, Jingbing Li^1,*, Jieren Cheng¹, Jixin Ma², Naveed Sadiq³, Baoru Han⁴, Qiang Geng⁵, Yang Ai⁵

CMC-Computers, Materials & Continua, Vol.61, No.2, pp. 889-910, 2019, DOI:10.32604/cmc.2019.06034

Abstract In order to solve the problem of patient information security protection in medical images, whilst also taking into consideration the unchangeable particularity of medical images to the lesion area and the need for medical images themselves to be protected, a novel robust watermarking algorithm for encrypted medical images based on dual-tree complex wavelet transform and discrete cosine transform (DTCWT-DCT) and chaotic map is proposed in this paper. First, DTCWT-DCT transformation was performed on medical images, and dot product was per-formed in relation to the transformation matrix and logistic map. Inverse transformation was undertaken to obtain encrypted medical images. Then, in… More >

Feng Li^1,2, Chaofeng Ou², Yan Gui^1,2,3,*, Lingyun Xiang^1,2

CMC-Computers, Materials & Continua, Vol.61, No.2, pp. 643-656, 2019, DOI:10.32604/cmc.2019.06094

Abstract The ability to quickly and intuitively edit digital content has become increasingly important in our everyday life. However, existing edit propagation methods for editing digital images are typically based on optimization with high computational cost for large inputs. Moreover, existing edit propagation methods are generally inefficient and highly time-consuming. Accordingly, to improve edit efficiency, this paper proposes a novel edit propagation method using a bilateral grid, which can achieve instant propagation of sparse image edits. Firstly, given an input image with user interactions, we resample each of its pixels into a regularly sampled bilateral grid, which facilitates efficient mapping from… More >

M.C. Ho Ba Tho¹

CMES-Computer Modeling in Engineering & Sciences, Vol.4, No.3&4, pp. 489-496, 2003, DOI:10.3970/cmes.2003.004.489

Abstract The objective of the paper is to address the methodology developed to model bone and joints with individualised geometric and material properties from medical image data. An atlas of mechanical properties of human bone has been investigated demonstrating individual differences. From these data, predictive relationships have been established between mechanical properties and quantitative data derived from measurements on medical images. Subsequently, geometric and numerical models of bones with individualised geometrical and mechanical properties have been developed from the same source of image data. The advantages of this modelling technique are its ability to study the `patient' specificity. This should be… More >

Dmitry S. Bulgarevich^1,*, Susumu Tsukamoto¹, Tadashi Kasuya², Masahiko Demura¹, Makoto Watanabe^1,3

The International Conference on Computational & Experimental Engineering and Sciences, Vol.22, No.2, pp. 122-122, 2019, DOI:10.32604/icces.2019.05271

Abstract The microstructure of steel greatly determines its mechanical properties/performance and holds information on chemical composition and processing history. Therefore, quantitative analysis of optical or SEM images on formed microstructure phases is one of the primary interests for metallurgy. So far, such analyses in laboratories are done manually by experts and are very time consuming. However, with modern microscopy techniques of automated image acquisitions over the large imaging areas and even by using of sample slicing for three-dimensional imaging, the amount of image data could be overwhelming for manual examinations. In this respect, there is a possibility that machine learning (ML)… More >

Osorio Rivera Fray León¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.7, No.2, pp. 63-76, 2008, DOI:10.3970/icces.2008.007.063

Abstract In the development context of a project about a system of selection uchuva for export by means of artificial vision whose objective is to provide an electromechanical system to able to select uchuvas by searching on its physical appearance, some algorithms have been developed to extract the necessary details beginning with the image of the acquired fruit using a camera. As a result, it must be able to determine if the visualized uchuva presents some symptom (insects, fungus, and deterioration) that indicates if it should be discharged. More >