Mohamed Meselhy Eltoukhy

Suez Canal University

This paper introduces a method for feature extraction from multiresolution representations (wavelet,curvelet) for classification of digital mammograms. The proposed method selects the features according to its capability to distinguish between different classes. The method starts with both performing wavelet and curvelet transform over mammogram im...

This paper presents a method for breast cancer diagnosis in digital mammogram images. Multi-resolution representations, wavelet or curvelet, are used to transform the mammogram images into a long vector of coefficients. A matrix is constructed by putting wavelet or curvelet coefficients of each image in row vector, where the number of rows is the n...

The study examined the implementation of artificial neural network (ANN) for the prediction and simulation of antibiotic degradation in aqueous solution by the Fenton process. A three-layer backpropagation neural network was optimized to predict and simulate the degradation of amoxicillin, ampicillin and cloxacillin in aqueous solution in terms of...

This paper presents an approach for breast cancer diagnosis in digital mammogram using curvelet transform. After decomposing the mammogram images in curvelet basis, a special set of the biggest coefficients is extracted as feature vector. The Euclidean distance is then used to construct a supervised classifier. The experimental results gave a 98.59...

This paper presents a comparative study between wavelet and curvelet transform for breast cancer diagnosis in digital mammogram. Using multiresolution analysis, mammogram images are decomposed into different resolution levels, which are sensitive to different frequency bands. A set of the biggest coefficients from each decomposition level is extrac...

Recently, scientists have widely utilized Artificial Intelligence (AI) approaches in intelligent agriculture to increase the productivity of the agriculture sector and overcome a wide range of problems. Detection and classification of plant diseases is a challenging problem due to the vast numbers of plants worldwide and the numerous diseases that...

Unmanned systems play a pivotal role in military surveillance, critical infrastructure protection, law enforcement, search and rescue operations, and border security, showcasing their multifaceted importance across diverse applications. Video fraud detection is integral to multimedia security, where our task involves the precise identification of m...

Super-resolution techniques are employed to enhance image resolution by reconstructing high-resolution images from one or more low-resolution inputs. Super-resolution is of paramount importance in the context of remote sensing, satellite, aerial, security and surveillance imaging. Super-resolution remote sensing imagery is essential for surveillanc...

This study focuses on addressing computational limits in smartphones by proposing an efficient authentication model that enables implicit authentication without requiring additional hardware and incurring less computational cost. The research explores various wrapper feature selection strategies and classifiers to enhance authentication accuracy wh...

This paper proposes a new robust watermarking method for securing color medical images, where the proposed method relies on combining Slant, Singular Value Decomposition (SVD), and quaternion Fourier-Transform (QFT). The stimulus behind this combination is to improve the invisibility and durability of the proposed method. First, the input cover ima...

Biometric technology is becoming increasingly prevalent in several vital applications that substitute traditional password and token authentication mechanisms. Recognition accuracy and computational cost are two important aspects that are to be considered while designing biometric authentication systems. Thermal imaging is proven to capture a uniqu...

Smartphones have now become an integral part of our everyday lives. User authentication on smartphones is often accomplished by mechanisms (like face unlock, pattern, or pin password) that authenticate the user’s identity. These technologies are simple, inexpensive, and fast for repeated logins. However, these technologies are still subject to assa...

With the advancement of information technology and economic globalization, the problem of supplier selection is gaining in popularity. The impact of supplier selection decisions made were quick and noteworthy on the healthcare profitability and total cost of medical equipment. Thus, there is an urgent need for decision support systems that address...

Pathologists need a lot of clinical experience and time to do the histopathological investigation. AI may play a significant role in supporting pathologists and resulting in more accurate and efficient histopathological diagnoses. Breast cancer is one of the most diagnosed cancers in women worldwide. Breast cancer may be detected and diagnosed usin...

Hajj is an International Islamic event held in Makkah, Saudi Arabia, which attracts more than three million pilgrims annually. With the increasing number of pilgrims, the demand for improving the quality of services during Hajj is increasing. Improving the quality of services to make Hajj safe and comfortable is the main objective of Hajj organizer...

Computer-aided systems for skin lesion diagnosis is a growing area of research. Recently, researchers have shown an increasing interest in developing computer-aided diagnosis systems. This paper aims to review, synthesize and evaluate the quality of evidence for the diagnostic accuracy of computer-aided systems. This study discusses the papers publ...

International Workshop on Machine Learning and Natural Language Processing for Cybersecurity as part of the program of the ACLing 2021: 5th International Conference on AI in Computational Linguistics June 4th-5th, 2021. For more details, visit this link https://easychair.org/cfp/ML-NLP4Cybersecurity Registration and submission guidelines of...

Breast cancer is one of the most prevalent cancer types with a high mortality rate in women worldwide. This devastating cancer still represents a worldwide public health concern in terms of high morbidity and mortality rates. The diagnosis of breast abnormalities is challenging due to different types of tissues and textural variations in intensity....

Aim: We aimed to explore the circulating expression profile of nine lncRNAs (MALAT1, HOTAIR, PVT1, H19, ROR, GAS5, ANRIL, BANCR, MIAT) in breast cancer (BC) patients relative to normal and risky individuals. Methods: Serum relative expressions of the specified long non-coding RNAs were quantified in 155 consecutive women, using quantitative reverse...

Masses are mammographic nonpalpable signs of breast cancer. These masses could be detected using screening mammography. This paper proposed a system utilizing orthogonal moment invariants (OMIs) features for mammographic masses detection and diagnosis. In this work, three sets of OMIs features were extracted. These OMIs features are Gaussian-Hermit...

Orthogonal moments are used to represent digital images with minimum redundancy. Orthogonal moments with fractional-orders show better capabilities in digital image analysis than integer-order moments. In this work, the authors present new fractional-order shifted Gegenbauer polynomials. These new polynomials are used to defined a novel set of orth...

The classical radial harmonic Fourier moments (RHFMs) and the quaternion radial harmonic Fourier moments (QRHFMs) are gray-scale and color image descriptors. The radial harmonic functions with integer orders are not able to extract fine features from the input images. In this paper, the authors derived novel fractional-order radial harmonic function...

Breast cancer is one of the major causes of women death worldwide. WHO organization has reported that 1 in every 12 women could be subjected to a breast abnormality during her lifetime. To increase survival rates, it is found that early detection of breast tumor is very critical. Mammography-based breast cancer screening is the leading technology t...

Breast cancer is one of the common cancer deaths in women worldwide. Early detection is the key to reduce the mortality rate. Clinical trials have shown that computer aided systems (CAD) have improved the accuracy of breast cancer detection. This paper proposed a highly accurate CAD system based on extracting highly significant features using exact...

This work introduces a computer-aided diagnosis (CAD) system for diagnosing liver cirrhosis in ultrasound (US) images. The proposed system uses a set of features obtained from different feature extraction methods. These features are the first order statistics (FOS), the fractal dimension (FD), the gray level co-occurrence matrix (GLCM), the Gabor f...

Accurate segregation of pectoral muscles is very crucial in breast cancer detection. Pectoral segmentation is a challenging task due to heterogeneous tissues densities, neighborhood complexities and breast shape variabilities. This paper presents an adaptive gamma correction method for pectoral suppression in mammograms. The proposed algorithm is a...

The aim of this paper is to introduce a robust CAD system that is able to increase the accuracy rate and reduce the false positive detection rate. This paper presents a system based on calculating the second order moment (variance) for the task of mass detection in digital mammogram. The goal is to develop a feature vector which is able to provide...

Abstract: Cancer remains one of the major concerns of deaths worldwide. Early detection is the key point in reducing the cancer mortality. Automatic systems are needed to assist radiologists in the cancer detection and diagnosis. Hence, there are strong needs for the development of computer aided diagnosis (CAD) systems which have the capability to...

Cancer remains one of the major concerns of deaths worldwide. Early detection is the key point in reducing the cancer mortality. Automatic systems are needed to assist radiologists in the cancer detection and diagnosis. Hence, there are strong needs for the development of computer aided diagnosis (CAD) systems which have the capability to help radi...

Breast cancer is one of the leading causes of death among women worldwide. Early detection of breast cancer significantly reduces the mortality rate. Computer aided diagnosis (CAD) systems assist the clinicians for early detection, however they are still far from perfection due to morphological diversity of abnormalities in mammograms. In this stud...

Whilst facial recognition systems are vulnerable to different acquisition conditions, most notably lighting effects and pose variations, their particular level of sensitivity to facial aging effects is yet to be researched. The face recognition vendor test (FRVT) 2012's annual statement estimated deterioration in the performance of face recognition...

cDNA microarray image processing becomes a viable branch of bioinformatics, its importance stems from the fact that it allows viewing and measuring tens of thousands of genes concurrently. Many techniques were introduced to develop and improve the mission of processing DNA microarray images. The aim of this study is to make a segmentation of the cD...

Early detection of breast cancer helps reducing the mortality rates. Mammography is very useful tool in breast cancer detection. But it is very difficult to separate different morphological features in mammographic images. In this study Morphological Component Analysis (MCA) method is used to extract different morphological aspects of mammographic...

A Brain computer interface (BCI) has introduced new scope and created a new period for developers and researchers giving alternative communication channels for paralysed peoples. Motor imagery refers to where EEG signals that being obtained while the subject is imagining or performing a motor response. This work is to examine this area from Machine...

This paper presents a method for classification of normal and abnormal tissues in mammograms using curvelet transform. The curvelet coefficients are represented into certain groups of coefficients, independently. Some statistical features are calculated for each group of coefficients. These statistical features are combined with features extracted...

Image texture analysis plays an important role in object detection and recognition in image processing. The texture analysis can be used for early detection of breast cancer by classifying the mammogram images into normal and abnormal classes. This study investigates breast cancer detection using texture features obtained from the grey level co-occ...

An early detection of abnormalities is the key point to improve the prognostic of breast Cancer. Masses are among the most frequent abnormalities. Their detection is however a very tedious and time-consuming task. This paper presents an automatic scheme to perform both detection and segmentation of breast masses. Firstly, the breast region is deter...

The work in this paper focuses on the automatic detection of masses in digital mammograms. The proposed system consists of two main stages; the first stage is the breast segmentation to remove the background and labels. The second stage is to determine the masses region. The proposed method utilizes the correlation between a typical mass region and...

This paper proposes a method for breast cancer diagnosis in digital mammogram. The article focuses on using texture analysis based on curvelet transform for the classification of tissues. The most discriminative texture features of regions of interest are extracted. Then, a nearest neighbor classifier based on Euclidian distance is constructed. The...

This paper presents an approach for breast cancer diagnosis in digital mammogram using curvelet transform. The motivation of this approach is the desire of using the advantages of curvelet transform into mammogram analysis. Curvelet provide stable, efficient and near-optimal representation of otherwise smooth objects having discontinuities along sm...

This paper introduces a new method of feature extraction from Wavelet coefficients for classification of digital mammograms. A matrix is constructed by putting Wavelet coefficients of each image of a building set as a row vector. The method consists then on selecting by threshold, the columns which will maximize the Euclidian distances between the...