Search results for: Amira S. Ashour

Items from 1 to 20 out of 57 results

article

Deep back propagation–long short-term memory network based upper-limb sEMG signal classification for automated rehabilitation

Ying Wang, Qun Wu, Nilanjan Dey, Simon Fong, more

Biocybernetics and Biomedical Engineering > 2020 > Vol. 40, no. 3 > 987--1001

Autonomous rehabilitation training for assisted patients with injured upper-limbs promotes the regenerative communication between muscle signals and brain consciousness. Surface electromyographic (sEMG) is a type of electrical signals of neuromuscular activity recorded by electrodes on the surface of the human body, which is widely applied for detecting gestures and stimuli reactions. Experimental...

article

Deep-segmentation of plantar pressure images incorporating fully convolutional neural networks

Dan Wang, Zairan Li, Nilanjan Dey, Amira S. Ashour, more

Biocybernetics and Biomedical Engineering > 2020 > Vol. 40, no. 1 > 546--558

Comfort shoe-last design relies on the key points of last curvature. Traditional plantar pressure image segmentation methods are limited to their local and global minimization issues. In this work, an improved fully convolutional networks (FCN) employing SegNet (SegNet+FCN 8 s) is proposed. The algorithm design and operation are performed using the visual geometry group (VGG). The method has high...

article

Plantar pressure image fusion for comfort fusion in diabetes mellitus using an improved fuzzy hidden Markov model

Zairan Li, Dan Wang, Nilanjan Dey, Amira S. Ashour, more

Biocybernetics and Biomedical Engineering > 2019 > Vol. 39, no. 3 > 742--752

Diabetes mellitus is a clinical syndrome caused by the interaction of genetic and environmental factors. The change of plantar pressure in diabetic patients is one of the important reasons for the occurrence of diabetic foot. The abnormal increase of plantar pressure is a predictor of the common occurrence of foot ulcers. The feature extraction of plantar pressure distribution will be beneficial to...

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Dual feature selection and rebalancing strategy using metaheuristic optimization algorithms in X-ray image datasets

Jinyan Li, Simon Fong, Lian-sheng Liu, Nilanjan Dey, more

Multimedia Tools and Applications > 2019 > 78 > 15 > 20913- 20933

The imbalance and multi-dimension are two common problems in the medical image datasets, which affect the performances of the image processing procedures. The traditional methods to solve these two problems are notoriously difficult. Accordingly, this work employed metaheuristic methods to optimize the rebalancing process of the imbalanced class distribution for further use in the feature selection...

article

Mathematical models and migrating birds optimization for robotic U-shaped assembly line balancing problem

Zixiang Li, Mukund Nilakantan Janardhanan, Amira S. Ashour, Nilanjan Dey

Neural Computing and Applications > 2019 > 31 > 12 > 9095-9111

Modern assembly line systems utilize robotics to replace human resources to achieve higher level of automation and flexibility. This work studies the task assignment and robot allocation in a robotic U-shaped assembly line. Two new mixed-integer programming linear models are developed to minimize the cycle time when the number of workstations is fixed. Recently developed migrating birds optimization...

article

Meta-KANSEI Modeling with Valence-Arousal fMRI Dataset of Brain

Fuqian Shi, Nilanjan Dey, Amira S. Ashour, Dimitra Sifaki-Pistolla, more

Cognitive Computation > 2019 > 11 > 2 > 227-240

Traditional KANSEI methodology is an important tool in the field of psychology to comprehend the concepts and meanings; it mainly focuses on semantic differential methods. Valence-arousal is regarded as a reflection of the KANSEI adjectives, which is the core concept in the theory of effective dimensions for brain recognition. From previous studies, it has been found that brain fMRI datasets can contain...

article

An optimized Mamdani FPD controller design of cardiac pacemaker

Mohamed I. Elnaggar, Amira S. Ashour, Yanhui Guo, Heba A. El-Khobby, more

Health Information Science and Systems > 2019 > 7 > 1 > 1-18

Cardiac pacemaker is a standard implantable medical electronic device for management and treatment of the heart rhythm disorders aiming to improved healthcare. Developing a new pacemaker based heart stimulation techniques has a vital role in preserving the patient’s life. This target inspired the present work to design a new Mamdani fuzzy proportional–derivative (FPD) controller of a cardiac pacemaker,...

article

Centroid tracking and velocity measurement of white blood cell in video

Mohamed Maher Ata, Amira S. Ashour, Yanhui Guo, Mustafa M. Abd Elnaby

Health Information Science and Systems > 2018 > 6 > 1 > 1-11

Automated blood cells tracking system has a vital role as the tracking process reflects the blood cell characteristics and indicates several diseases. Blood cells tracking is challenging due to the non-rigid shapes of the blood cells, and the variability in their videos along with the existence of different moving objects in the blood. To tackle such challenges, we proposed a green star based centroid...

article

Ensemble of subspace discriminant classifiers for schistosomal liver fibrosis staging in mice microscopic images

Amira S. Ashour, Yanhui Guo, Ahmed Refaat Hawas, Guan Xu

Health Information Science and Systems > 2018 > 6 > 1 > 1-10

Schistosomiasis is one of the dangerous parasitic diseases that affect the liver tissues leading to liver fibrosis. Such disease has several levels, which indicate the degree of fibrosis severity. To assess the fibrosis level for diagnosis and treatment, the microscopic images of the liver tissues were examined at their different stages. In the present work, an automated staging method is proposed...

article

Optimal choice of k-mer in composition vector method for genome sequence comparison

Subhram Das, Tamal Deb, Nilanjan Dey, Amira S. Ashour, more

Genomics > 2018 > 110 > 5 > 263-273

Several proteins and genes are members of families that share a public evolutionary. In order to outline the evolutionary relationships and to recognize conserved patterns, sequence comparison becomes an emerging process. The current work investigates critically the k-mer role in composition vector method for comparing genome sequences. Generally, composition vector methods using k-mer are applied...

article

Comparative study of multiclass classification methods on light microscopic images for hepatic schistosomiasis fibrosis diagnosis

Amira S. Ashour, Ahmed Refaat Hawas, Yanhui Guo

Health Information Science and Systems > 2018 > 6 > 1 > 1-12

Hepatic schistosomiasis is a prolonged disease resulting mainly from the solvable egg antigen of schistosomiasis infection due to the host’s granulomatous cell-mediated immune. Irreversible fibrosis results from the progress of the schistosomal hepatopathy. Sensitive diagnosis of this disease is based on the investigation of the microscopy images, liver tissues, and egg identification. Early diagnosis...

article

A hybrid dermoscopy images segmentation approach based on neutrosophic clustering and histogram estimation

Amira S. Ashour, Yanhui Guo, Enver Kucukkulahli, Pakize Erdogmus, more

Applied Soft Computing > 2018 > 69 > C > 426-434

In this work, a novel skin lesion detection approach, called HBCENCM, is proposed using histogram-based clustering estimation (HBCE) algorithm to determine the required number of clusters in the neutrosophic c-means clustering (NCM) method. Initially, the dermoscopic images are mapped into the neutrosophic domain over three memberships, namely true, indeterminate, and false subsets. Then, an NCM algorithm...

article

A novel optimized neutrosophic k-means using genetic algorithm for skin lesion detection in dermoscopy images

Amira S. Ashour, Ahmed Refaat Hawas, Yanhui Guo, Maram A. Wahba

Signal, Image and Video Processing > 2018 > 12 > 7 > 1311-1318

This paper implemented a new skin lesion detection method based on the genetic algorithm (GA) for optimizing the neutrosophic set (NS) operation to reduce the indeterminacy on the dermoscopy images. Then, k-means clustering is applied to segment the skin lesion regions. Therefore, the proposed method is called optimized neutrosophic k-means (ONKM). On the training images set, an initial value of $$\alpha...

article

Medical cyber-physical systems: A survey

Nilanjan Dey, Amira S. Ashour, Fuqian Shi, Simon James Fong, more

Journal of Medical Systems > 2018 > 42 > 4 > 1-13

Medical cyber-physical systems (MCPS) are healthcare critical integration of a network of medical devices. These systems are progressively used in hospitals to achieve a continuous high-quality healthcare. The MCPS design faces numerous challenges, including inoperability, security/privacy, and high assurance in the system software. In the current work, the infrastructure of the cyber-physical systems...

article

A new hybrid classifier selection model based on mRMR method and diversity measures

Soraya Cheriguene, Nabiha Azizi, Nilanjan Dey, Amira S. Ashour, more

International Journal of Machine Learning and Cybernetics > 2019 > 10 > 5 > 1189-1204

Classifier subset selection becomes an important stage in multiple classifier systems (MCSs) design to reduce the number of classifiers by eliminating the identical and inaccurate members. Minimum redundancy maximum relevance (mRMR) is a feature selection method that compromises between relevance and redundancy by obliterating similar members and keeping the most pertinent ones. In the current work,...

article

Hybrid feature extraction techniques for microscopic hepatic fibrosis classification

Dalia S. Ashour, Dina M. Abou Rayia, Mohamed Maher Ata, Amira S. Ashour, more

Microscopy Research and Technique > 81 > 3 > 338 - 347

Chronic liver diseases' hallmark is the fibrosis that results in liver function failure in advanced stages. One of the serious parasitic diseases affecting the liver tissues is schistosomiasis. Immunologic reactions to Schistosoma eggs leads to accumulation of collagen in the hepatic parenchyma causing fibrosis. Thus, monitoring and reporting the staging of the histopathological information related...

article

Dental diagnosis from X-Ray images: An expert system based on fuzzy computing

Le Hoang Son, Tran Manh Tuan, Hamido Fujita, Nilanjan Dey, more

Biomedical Signal Processing and Control > 2018 > 39 > C > 64-73

Computerized medical diagnosis systems from X-Ray images are of great interest to physicians for accurate decision making of possible diseases and treatments. Subclinical disease has no recognizable clinical findings, thus it is desirable to segment the dental X-Ray image into groups and then use soft computing methods to check the possibility of whether or not any disease occurs therein.The current...

article

A novel glomerular basement membrane segmentation using neutrsophic set and shearlet transform on microscopic images

Yanhui Guo, Amira S. Ashour, Baiqing Sun

Health Information Science and Systems > 2017 > 5 > 1 > 1-9

Purpose Glomerular basement membrane segmentation is an ultimate step in several image processing applications for kidney diseases and abnormalities in microscopic images. However, extracting the glomerular basement membrane (GBM) regions accurately is considered challenging because of the large variants in the microscopic images. The contribution of this work is to propose a computer-aided detection...

article

Combined empirical mode decomposition and texture features for skin lesion classification using quadratic support vector machine

Maram A. Wahba, Amira S. Ashour, Sameh A. Napoleon, Mustafa M. Abd Elnaby, more

Health Information Science and Systems > 2017 > 5 > 1 > 1-13

Purpose Basal cell carcinoma is one of the most common malignant skin lesions. Automated lesion identification and classification using image processing techniques is highly required to reduce the diagnosis errors. Methods In this study, a novel technique is applied to classify skin lesion images into two classes, namely the malignant Basal cell carcinoma and the benign nevus. A hybrid combination...

article

Modified cuckoo search algorithm in microscopic image segmentation of hippocampus

Shouvik Chakraborty, Sankhadeep Chatterjee, Nilanjan Dey, Amira S. Ashour, more

Microscopy Research and Technique > 80 > 10 > 1051 - 1072

Microscopic image analysis is one of the challenging tasks due to the presence of weak correlation and different segments of interest that may lead to ambiguity. It is also valuable in foremost meadows of technology and medicine. Identification and counting of cells play a vital role in features extraction to diagnose particular diseases precisely. Different segments should be identified accurately...

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Search results for: Amira S. Ashour

Deep back propagation–long short-term memory network based upper-limb sEMG signal classification for automated rehabilitation

Deep-segmentation of plantar pressure images incorporating fully convolutional neural networks

Plantar pressure image fusion for comfort fusion in diabetes mellitus using an improved fuzzy hidden Markov model

Dual feature selection and rebalancing strategy using metaheuristic optimization algorithms in X-ray image datasets

Mathematical models and migrating birds optimization for robotic U-shaped assembly line balancing problem

Meta-KANSEI Modeling with Valence-Arousal fMRI Dataset of Brain

An optimized Mamdani FPD controller design of cardiac pacemaker

Centroid tracking and velocity measurement of white blood cell in video

Ensemble of subspace discriminant classifiers for schistosomal liver fibrosis staging in mice microscopic images

Optimal choice of k-mer in composition vector method for genome sequence comparison

Comparative study of multiclass classification methods on light microscopic images for hepatic schistosomiasis fibrosis diagnosis

A hybrid dermoscopy images segmentation approach based on neutrosophic clustering and histogram estimation

A novel optimized neutrosophic k-means using genetic algorithm for skin lesion detection in dermoscopy images

Medical cyber-physical systems: A survey

A new hybrid classifier selection model based on mRMR method and diversity measures

Hybrid feature extraction techniques for microscopic hepatic fibrosis classification

Dental diagnosis from X-Ray images: An expert system based on fuzzy computing

A novel glomerular basement membrane segmentation using neutrsophic set and shearlet transform on microscopic images

Combined empirical mode decomposition and texture features for skin lesion classification using quadratic support vector machine

Modified cuckoo search algorithm in microscopic image segmentation of hippocampus

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