Omar S. Al-Kadi

Omar S. Al-Kadi
University of Jordan | UJ · King Abdullah II School for Information Technology

PhD

About

51
Publications
38,383
Reads
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851
Citations
Citations since 2016
31 Research Items
659 Citations
2016201720182019202020212022020406080100
2016201720182019202020212022020406080100
2016201720182019202020212022020406080100
2016201720182019202020212022020406080100
Introduction
I am a professor in Computational Imaging at the University of Jordan. I was also a Fulbright visiting scholar at Yale University and a visiting professor at the Swiss Federal Institute of Technology Lausanne (EPFL). Before that, I worked as a postdoctoral research fellow at the Institute of Biomedical Engineering at the University of Oxford (Oxford, UK), and the Biomedical Imaging group within the Centre for Vision, Speech and Signal Processing at the University of Surrey (Guildford, UK).
Additional affiliations
September 2017 - June 2018
Yale University
Position
  • Professor
Description
  • http://people.yale.edu/search/omar_al-kadi.profile
July 2015 - July 2016
École Polytechnique Fédérale de Lausanne
Position
  • Professor
Description
  • https://miplab.epfl.ch/index.php/people/alumni/alkadi
November 2014 - present
University of Jordan
Position
  • Professor (Associate)
Education
January 2006 - January 2010
University of Sussex
Field of study
  • Engineering & Informatics
February 2002 - November 2003
University of Canberra
Field of study
  • Information Technology
September 1996 - June 2001
Cairo University
Field of study
  • Biomedical Engineering

Publications

Publications (51)
Article
Full-text available
This paper presents the potential for fractal analysis of time sequence contrast-enhanced (CE) computed tomography (CT) images to differentiate between aggressive and nonaggressive malignant lung tumors (i.e., high and low metabolic tumors). The aim is to enhance CT tumor staging prediction accuracy through identifying malignant aggressiveness of l...
Article
Full-text available
Providing an improved technique which can assist pathologists in correctly classifying meningioma tumours with a significant accuracy is our main objective. The proposed technique, which is based on optimum texture measure combination, inspects the separability of the RGB colour channels and selects the channel which best segments the cell nuclei o...
Article
Full-text available
Tissue texture is known to exhibit a heterogeneous or non-stationary nature; therefore using a single resolution approach for optimum classification might not suffice. A clinical decision support system that exploits the subbands’ textural fractal characteristics for best bases selection of meningioma brain histopathological image classification is...
Article
Full-text available
Intensity variations in image texture can provide powerful quantitative information about physical properties of biological tissue. However, tissue patterns can vary according to the utilized imaging system and are intrinsically correlated to the scale of analysis. In the case of ultrasound, the Nakagami distribution is a general model of the ultra...
Article
Full-text available
Assessment of tumor tissue heterogeneity via ultrasound has recently been suggested as a method for predicting early response to treatment. The ultrasound backscattering characteristics can assist in better understanding the tumor texture by highlighting the local concentration and spatial arrangement of tissue scatterers. However, it is challengin...
Article
The surge in cyber-attacks has driven demand for robust Intrusion detection systems (IDSs) to protect underlying data and sustain availability of network services. Detecting and classifying multiple type of attacks requires robust machine learning approaches that can analyze network traffic and take appropriate measures. Traffic data usually consis...
Article
Full-text available
Cyber-attacks and unauthorized application usage have increased due to the extensive use of Internet services and applications over computer networks, posing a threat to the service’s availability and consumers’ privacy. A network Intrusion Detection System (IDS) aims to detect aberrant traffic behavior that firewalls cannot detect. In IDSs, dimens...
Article
Full-text available
Conditional Generative Adversarial Network (cGAN) is a general purpose approach for many image-to-image translation tasks, which aims to translate images from one form to another resulting in high-quality translated images. In this paper, the loss function of the cGAN model is modified by combining the adversarial loss of state-of-the-art Generativ...
Article
Full-text available
The data presented in this article deals with the problem of brain tumor image translation across different modalities. The provided dataset represents unpaired brain magnetic resonance (MR) and computed tomography (CT) image data volumes of 20 patients. This includes 179 two-dimensional (2D) axial MR and CT images. The MR cases are acquired using...
Article
Full-text available
Medical image acquisition plays a significant role in the diagnosis and management of diseases. Magnetic Resonance (MR) and Computed Tomography (CT) are considered two of the most popular modalities for medical image acquisition. Some considerations, such as cost and radiation dose, may limit the acquisition of certain image modalities. Therefore,...
Article
Full-text available
Deep learning has emerged as a new area of machine learning research. It is an approach that can learn features and hierarchical representation purely from data and has been successfully applied to several fields such as images, sounds, text and motion. The techniques developed from deep learning research have already been impacting the research on...
Article
Full-text available
Deep learning has emerged as a new area of machine learning research. It is an approach that can learn features and hierarchical representation purely from data and has been successfully applied to several fields such as images, sounds, text and motion. The techniques developed from deep learning research have already been impacting the research on...
Article
Health challenges represent one of the long-standing issues in the Arab region that hinder its ability to develop. Prevalence of diseases such as cardiovascular diseases, liver cirrhosis and cancer among many others has contributed to the deteriorated health status across the region leading to lower life expectancy compared to other regions. For in...
Article
The surge in cyber-attacks has driven demand for robust Intrusion detection systems (IDSs) to protect underlying data and sustain availability of network services. Detecting and classifying multiple type of attacks requires robust machine learning approaches that can analyze network traffic and take appropriate measures. Traffic data usually consis...
Preprint
Full-text available
In recent years, Knowledge Management Systems (KMS) have drawn remarkable attention. However, there is no common understanding of how a knowledge management system should look like or where the corresponding research should be directed at. Based on a number of essential requirements that a KMS should satisfy, this report introduces some possible re...
Article
Full-text available
Purpose To investigates whether the FD of non-small cell lung cancer (NSCLC) on CT predicts tumor stage and uptake on ¹⁸F-fluorodeoxyglucose positron emission tomography. Material and methods The FD within a tumor region was determined using a box counting algorithm and compared to the lymph node involvement (NI) and metastatic involvement (MI) an...
Article
Full-text available
Online social networks have established virtual platforms enabling people to express their opinions, interests and thoughts in a variety of contexts and domains, allowing legitimate users as well as spammers and other untrustworthy users to publish and spread their content. Hence, it is vital to have an accurate understanding of the contex‑tual con...
Preprint
Full-text available
Online Social Networks(OSNs) have established virtual platforms enabling people to express their opinions, interests and thoughts in a variety of contexts and domains, allowing legitimate users as well as spammers and other untrustworthy users to publish and spread their content. Hence, the concept of social trust has attracted the attention of inf...
Preprint
Full-text available
An important aspect for an improved cardiac functional analysis is the accurate segmentation of the left ventricle (LV). A novel approach for fully-automated segmentation of the LV endocardium and epicardium contours is presented. This is mainly based on the natural physical characteristics of the LV shape structure. Both sides of the LV boundaries...
Preprint
Full-text available
Assessing tumor tissue heterogeneity via ultrasound has recently been suggested for predicting early response to treatment. The ultrasound backscattering characteristics can assist in better understanding the tumor texture by highlighting local concentration and spatial arrangement of tissue scatterers. However, it is challenging to quantify the va...
Article
Full-text available
An important aspect for an improved cardiac functional analysis is the accurate segmentation of the left ventricle (LV). A novel approach for fully-automated segmentation of the LV endocardium and epicardium contours is presented. This is mainly based on the natural physical characteristics of the LV shape structure. Both sides of the LV boundaries...
Article
Full-text available
The role of Ki-67 index in determining the prognosis and management of gastroenteropancreatic neuroendocrine tumors (GEP-NETs) has become more important yet presents a challenging assessment dilemma. Although the precise method of Ki-67 index evaluation has not been standardized, several methods have been proposed, and each has its pros and cons. O...
Preprint
Full-text available
Effective ultrasound tissue characterization is usually hindered by complex tissue structures. The interlacing of speckle patterns complicates the correct estimation of backscatter distribution parameters. Nakagami parametric imaging based on localized shape parameter mapping can model different backscattering conditions. However, performance of th...
Chapter
Full-text available
A novel approach for fully-automated segmentation of the left ventricle (LV) endocardial and epicardial contours is presented. This is mainly based on the natural physical characteristics of the LV shape structure. Both sides of the LV boundaries exhibit natural elliptical curvatures by having details on various scales, i.e. exhibiting fractal-like...
Book
Full-text available
https://www.elsevier.com/books/title/author/9780128121337 Biomedical Texture Analysis: Fundamentals, Applications, Tools and Challenges describes the fundamentals and applications of biomedical texture analysis (BTA) for precision medicine. It defines what biomedical textures (BTs) are and why they require specific image analysis design approaches...
Article
Full-text available
Meningioma brain tumour discrimination is challenging as many histological patterns are mixed between the different subtypes. In clinical practice, dominant patterns are investigated for signs of specific meningioma pathology; however the simple observation could result in inter- and intra-observer variation due to the complexity of the histopathol...
Chapter
Full-text available
Discriminative visual patterns in tissue texture tends to be fuzzy, and clinicians are usually faced with a certain degree of diagnostic uncertainty. Understanding how biological tissue complexity is manifested at different levels of resolution can contribute toward an effective texture analysis approach. The fractal dimension can quantify the geom...
Conference Paper
Full-text available
The number density of scatterers in tumor tissue contribute to a heterogeneous ultrasound speckle pattern that can be difficult to discern by visual observation. Such tumor stochastic behavior becomes even more challenging if the tumor texture heterogeneity itself is investigated for changes related to response to chemotherapy treatment. Here we de...
Conference Paper
Full-text available
Effective ultrasound tissue characterization is usually hindered by complex tissue structures. The interlacing of speckle patterns complicates the correct estimation of backscatter distribution parameters. Nakagami parametric imaging based on localized shape parameter mapping can model different backscattering conditions. However, performance of th...
Chapter
The structural complexity of brain tumor tissue represents a major challenge for effective histopathological diagnosis. Tumor vasculature is known to be heterogeneous and mixtures of patterns are usually present. Therefore, extracting key descriptive features for accurate quantification is not a straightforward task. Several steps are involved in t...
Chapter
Brain parenchyma microvasculature is set in disarray in the presence of tumors, and malignant brain tumors are among the most vascularized neoplasms in humans. As microvessels can be easily identified in histologic specimens, quantification of microvascularity can be used alone or in combination with other histological features to increase the unde...
Article
Full-text available
Recently, telecommunication companies have been paying more attention toward the problem of identification of customer churn behavior. In business, it is well known for service providers that attracting new customers is much more expensive than retaining existing ones. Therefore, adopting accurate models that are able to predict customer churn can...
Article
Full-text available
Customer churn is an important and challenging problem that faces telecommunication companies worldwide. Recently, companies have been investing more in developing accurate prediction models which can forecast which customers axe about ending their subscriptions or switching to another competitor service provider. These models can help Customer Rel...
Article
Full-text available
Road traffic density has always been a concern in large cities around the world, and many approaches were developed to assist in solving congestions related to slow traffic flow. This work proposes a congestion rate estimation approach that relies on real-time video scenes of road traffic, and was implemented and evaluated on eight different hotspo...
Conference Paper
Full-text available
In this work, we propose a methodology for segmenting glands automatically in digitized images of histopathological prostate tissue for grade classification. Gleason grading describes the abnormality of cancer cells and their degree of aggressiveness by using numerical scale from grade 1 that represents benign tissues through grade 5 for tissues ch...
Article
One of the major problems that face people daily is the increased number of vehicles in cities. This increase greatly leads to the presence of traffic jams and the depletion of drivers' important time. It also adds pressure on people who are in charge of managing traffic and controlling the flow of cars from one place to another. The source of pres...
Chapter
Advances in Web technologies have brought about a massive increase in online businesses, but security has significantly lagged behind. We and others argue that governments can and should play a major role in providing a reliable and secure environment for online businesses because they have a major stake in growing the economy. Our finding from pre...
Conference Paper
Nuclei counting in epithelial cells is an indication for tumor proliferation rate which is useful to rank tumors and select an appropriate treatment schedule for the patient. However, due to the high interand intra- observer variability in nuclei counting, pathologists seek a deterministic proliferation rate estimate. Histology tissue contains epit...
Article
Full-text available
The aim of this study was to investigate the usefulness of texture analysis in the characterization of oral cancers involving the buccal mucosa and to assess its effectiveness in differentiating between the various grades of the tumour. Contrast enhanced CT examination was carried out in 21 patients with carcinoma of the buccal mucosa who had conse...
Conference Paper
Full-text available
Radio Frequency Identification (RFID) is one of the most popular Automatic Identification and Data Capture (AIDC) technologies that facilitate objects identification and information exchange over relatively small and widely separated entities. In this paper, the main aim is to address the privacy and security challenges that RFID Access Control Sys...
Conference Paper
Full-text available
This paper aims to compare between four different types of feature extraction approaches in terms of texture segmentation. The feature extraction methods that were used for segmentation are Gabor filters (GF), Gaussian Markov random fields (GMRF), run-length matrix (RLM) and co-occurrence matrix (GLCM). It was shown that the GF performed best in te...
Article
Full-text available
Noise is one of the major problems that hinder an effective texture analysis of disease in medical images, which may cause variability in the reported diagnosis. In this paper seven texture measurement methods (two wavelet, two model and three statistical based) were applied to investigate their susceptibility to subtle noise caused by acquisition...
Conference Paper
Full-text available
With the heterogeneous nature of tissue texture, using a single resolution approach for optimum classification might not suffice. In contrast, a multiresolution wavelet packet analysis can decompose the input signal into a set of frequency subbands giving the opportunity to characterise the texture at the appropriate frequency channel. An adaptive...
Thesis
Full-text available
Medical imaging represents the utilisation of technology in biology for the purpose of noninvasively revealing the internal structure of the organs of the human body. It is a way to improve the quality of the patient’s life through a more precise and rapid diagnosis, and with limited side-effects, leading to an effective overall treatment procedure...
Conference Paper
Full-text available
Five different texture methods are used to investigate their susceptibility to subtle noise occurring in lung tumor Computed Tomography (CT) images caused by acquisition and reconstruction deficiencies. Noise of Gaussian and Rayleigh distributions with varying mean and variance was encountered in the analyzed CT images. Fisher and Bhattacharyya dis...
Conference Paper
Full-text available
This paper aims to improve the accuracy of texture classification based on extracting texture features using five different texture measures and classifying the patterns using a naive Bayesian classifier. Three statistical-based and two model-based methods are used to extract texture features from eight different texture images, then their accuracy...
Poster
Full-text available
AIM The fractal dimension (FD) of a structure provides a measure of its complexity. This pilot study aims to determine FD values for lung cancers visualised on Computed Tomography (CT) and to assess the potential for tumour FD measurements to provide an index of tumour aggression. METHOD Pre-and post-contrast CT images of the thorax acquired from 1...

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