Anke Meyer-Base

Anke Meyer-Base
Florida State University | FSU · Department of Scientific Computing

Ph.D. Electrical Engineering

About

376
Publications
53,637
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
3,798
Citations
Citations since 2016
67 Research Items
1924 Citations
2016201720182019202020212022050100150200250300350
2016201720182019202020212022050100150200250300350
2016201720182019202020212022050100150200250300350
2016201720182019202020212022050100150200250300350
Additional affiliations
March 2008 - present
Florida State University
Position
  • Professor (Full)
January 2001 - present
Florida State University
Position
  • Professor (Full)
Education
July 1990 - February 1995
Technische Universität Darmstadt
Field of study
  • Electrical and Computer Engineering

Publications

Publications (376)
Article
Full-text available
The development of devices for the Internet of Things (IoT) requires the rapid prototyping of different hardware configurations. In this paper, a modular hardware platform allowing to prototype, test and even implement IoT appliances on low-cost reconfigurable devices is presented. The proposed platform, named Dracon, includes a Z80-clone microproc...
Conference Paper
Controlling the dynamics of large-scale neural circuits might play an important role in aberrant cognitive functioning as found in Alzheimer's disease (AD). Analyzing the disease trajectory changes is of critical relevance when we want to get an understanding of the neurodegenerative disease evolution. Advanced control theory offers a multitude of...
Article
Full-text available
In this paper, based on the pathogenesis of Alzheimer's disease, we investigate a stochastic mathematical model, focusing on the dynamics of β‐amyloid (Aβ) plaques, Aβ oligomers, PrPC proteins, and the Aβ‐x‐PrP C complex. Within the framework of the Lyapunov method, we first show existence and uniqueness of global positive solution of the model and...
Article
Full-text available
Computer‐aided diagnosis (CAD) systems have become an important tool in the assessment of breast tumors with magnetic resonance imaging (MRI). CAD systems can be used for the detection and diagnosis of breast tumors as a “second opinion” review complementing the radiologist's review. CAD systems have many common parts, such as image preprocessing,...
Article
Full-text available
Recent advances in artificial intelligence (AI) and deep learning (DL) have impacted many scientific fields including biomedical maging. Magnetic resonance imaging (MRI) is a well-established method in breast imaging with several indications including screening, staging, and therapy monitoring. The rapid development and subsequent implementation of...
Article
Full-text available
The change of parameters may influence the dynamic behaviors of epidemic diseases. Biological system parameters can also be changed due to diverse uncertainties such as lack of data and errors in the statistical approach. The problem of how to define and decide the optimal‐control strategies of epidemic diseases with imprecise parameters deserves f...
Chapter
Full-text available
Imbalanced datasets constitute a challenge in medical-image processing and machine learning in general. When the available training data is highly imbalanced, the risk for a classifier to find the trivial solution increases dramatically. To control the risk, an estimate on the prior class probabilities is usually required. In some medical datasets,...
Conference Paper
Full-text available
The advancement of Internet of Things (IoT) technologies, such as low-cost embedded single board computers which integrate sensors, communication hardware, and processing power in one unit, has given more traction to the concept of “Smart Cities.” Having cheaper processing power at their disposal, the sensing units are capable of gathering increasi...
Conference Paper
Full-text available
Big data has been one of the hottest topics of scientific discussions in the recent years. In early 2000s, an industry analyst attempted to describe big data as the three Vs: Volume, Velocity, and Variability. With the new technologies such as Hadoop, it is now feasible to store and use extremely large volumes of data that comes in at an unpreceden...
Article
This paper focuses on numerical approximation of the basic reproduction number R0, which is the threshold defined by the spectral radius of the next-generation operator in epidemiology. Generally speaking, R0 cannot be explicitly calculated for most age-structured epidemic systems. In this paper, for a deterministic age-structured epidemic system a...
Conference Paper
Full-text available
Reducing a graph model is extremely important for the dynamical analysis of large-scale networks. In order to approximate the behavior of such a system it is helpful to be able to simplify the model. In this paper, the graph reduction model is introduced. This method is based on removing edges that close independent cycles in the graph. We apply th...
Conference Paper
Full-text available
Leader-follower controllability in brain networks which are affected neurodegenerative diseases can provide important biomarkers relevant for disease evolution. The brain network is viewed as a dynamic system where the nodes interact via neighbor-based Laplacian feedback rules. The network has cooperative connections between the nodes described by...
Article
Background: Detecting pathological breast calcifications remains challenging. Based on recent studies, contrast-enhanced spectral mammography (CESM) was shown to be superior compared to full-field digital mammogra-phy (FFDM). Purpose: To evaluate the diagnostic accuracy of CESM in suspicious breast calcifications and its impact on surgical decision...
Article
Full-text available
Nonmass-enhancing (NME) lesions constitute a diagnostic challenge in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast. Computer-aided diagnosis (CAD) systems provide physicians with advanced tools for analysis, assessment, and evaluation that have a significant impact on the diagnostic performance. Here, we propose a new...
Article
Full-text available
The new concept called pinning observability is proposed for competitive neural networks with different time-scales and a distributed observer structure, which is determined to estimate the states of this large scale network. This network observer has local distinct sub-observers that process local information at the node level but exchange their s...
Article
Purpose: The aim of this study was to assess the potential of machine learning with multiparametric magnetic resonance imaging (mpMRI) for the early prediction of pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) and of survival outcomes in breast cancer patients. Materials and methods: This institutional review board-approv...
Article
Full-text available
In this study, a multi-stage optimization procedure is proposed to develop deep neural network models which results in a powerful deep learning pipeline called intelligent deep learning (iDeepLe). The proposed pipeline is then evaluated by a challenging real-world problem, the modeling of the spectral acceleration experienced by a particle during e...
Chapter
Full-text available
Accurate methods for computer aided diagnosis of breast cancer increase accuracy of detection and provide support to physicians in detecting challenging cases. In dynamic contrast enhancing magnetic resonance imaging (DCE-MRI), motion artifacts can appear as a result of patient displacements. Non-linear deformation algorithms for breast image regis...
Conference Paper
This paper aims at implementing novel biomarkers extracted from functional magnetic resonance imaging (fMRI) images taken at resting-state using convolutional neural networks (CNN) to predict relapse in heavy smoker subjects. In this regard, two classes of subjects were studied. The first class contains 19 subjects that took the drug N-acetylcystei...
Article
Background and Aim In patients undergoing neoadjuvant chemotherapy for breast cancer the achievement of a pathological complete response (pCR) is associated with a significantly improved disease-free and overall survival. Therefore, accurate means to predict treatment response as early as possible are desirable to identify women who don't benefit...
Conference Paper
According to NASA's report on the technologies that could reduce external aircraft noise by 10 dB, a challenge equally as important as finding approaches on airframe noise reduction is the demand to bring up strategies by which airframe noise can be predicted both accurately and rapidly. One of the components of the overall airframe noise is the se...
Conference Paper
Massive Online Open Course (MOOC) is a scalable, free or affordable online course which emerged as one of the fastest growing distance education platforms in the past decade. One of the biggest challenges that threatens distance education is abnormality in the overall level of consciousness of students while they are taking the course. In this pape...
Chapter
Full-text available
Computer aided applications in Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) are increasingly gaining attention as important tools to asses the risk of breast cancer. Chest wall detection and whole breast segmentation require effective solutions to increase the potential benefits of computer aided tools for tumor detection. Here we...
Article
Full-text available
This paper aims at developing new theory-driven biomarkers by implementing and evaluating novel techniques from resting-state scans that can be used in relapse prediction for nicotine-dependent patients and future treatment efficacy. Two classes of patients were studied. One class took the drug N-acetylcysteine and the other class took a placebo. T...
Conference Paper
Full-text available
Diagnostically challenging breast tumors and Non-Mass-Enhancing (NME) lesions are often characterized by spatial and temporal heterogeneity, thus difficult to detect and classify. Differently from mass enhancing tumors they have an atypical temporal enhancement behavior that does not enable a straight-forward lesion classification into benign or ma...
Conference Paper
Full-text available
The Internet of Things concept is described as a network of interconnected physical objects capable of gather, process, and communicate information about their environment, and potentially affect the physical world around them through their sensors, embedded processors, communication modules, and actuators, respectively. Such a network can provide...
Conference Paper
Full-text available
In today's increasingly divided political climate there is a need for a tool that can compare news articles and organizations so that a user can receive a wider range of views and philosophies. NewsAnalyticalToolkit allows a user to compare news sites and their political articles by coverage, mood, sentiment, and objectivity. The user can sort thro...
Conference Paper
Full-text available
Neo-adjuvant chemotherapy (NAC) is the treatment of choice in patients with locally advanced breast cancer to reduce tumor burden, and potentially enable breast conservation. Response to treatment is assessed by histopathology from surgical specimen, a pathological complete response (pCR), or a minimal residual disease are associated with an improv...
Conference Paper
Full-text available
Imaging connectomics emerged as an important field in modern neuroimaging to represent the interaction of structural and functional brain areas. Static graph networks are the mathematical structure to capture these interactions modeled by Pearson correlations between the representative area signals. Dynamical functional resting state networks seen...
Article
Full-text available
Non-mass enhancing lesions (NME) constitute a diagnostic challenge in dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) of the breast. Computer Aided Diagnosis (CAD) systems provide physicians with advanced tools for analysis, assessment and evaluation that have a significant impact on the diagnostic performance. Here, we propose a new...
Article
Full-text available
Recent exponential growth of investors in stock markets brings the idea to develop a predictive model to forecast the total risk of investment in stock markets. In this paper, an evolutionary approach was proposed to predict the total risk in stock investment based on an S&P 500 database in a time period of 1991-2010 employing a multi-objective gen...
Article
Full-text available
In the publication of this article (Cao et al. in Adv. Differ. Equ. 2017:307, 2017), there was an error that the author Anke Meyer-Baese was missing. Anke Meyer-Baese contributed towards the methodological design, study concept, the biological interpretation of the parameters of the systems and the writing of the system’s description. Omission is d...
Article
Full-text available
Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly understood and treatment strat...
Conference Paper
We consider resting-state Functional Magnetic Resonance Imaging (fMRI) of two classes of patients: one that took the drug N-acetylcysteine (NAC) and the other one a placebo before and after a smoking cessation treatment. Our goal was to classify the relapse in nicotine-dependent patients as treatment or non-treatment based on their fMRI scans. 80%...
Conference Paper
Full-text available
An important problem in modern therapeutics at the proteomic levelremains to identify therapeutic targets ina plentitude of high-throughput data from experiments relevant to a variety of diseases. This paper presentsthe application of novel modern control concepts, such as pinningcontrollability and observability applied tothe glioma cancer stem ce...
Article
Full-text available
In this paper, the problem of robust state estimation for discrete-time stochastic Markov jump neural networks with discrete and distributed time-varying delays is investigated based on dissipativity and passivity theory. The parameters of the neural networks are subject to the switching from one mode to another according to a Markov chain. By usin...
Article
A cascaded integrator-comb (CIC)-based decimator is proposed, which consists of an area-efficient structure aided with an embedded simplified Chebyshev-sharpened section. Taking traditional CIC filters as a reference, the proposed scheme fulfils two important goals: (i) it improves the worst-case aliasing rejection and (ii) it preserves a low-compl...
Article
Computer-aided diagnosis (CAD) systems constitute a powerful tool for early diagnosis of Alzheimer's disease (AD), but limitations on interpretability and performance exist. In this work, a fully automatic CAD system based on supervised learning methods is proposed to be applied on segmented brain magnetic resonance imaging (MRI) from Alzheimer's d...
Conference Paper
Diagnostically challenging lesions pose a challenge both for the radiological reading and also for current CAD systems. They are not well-defined in both morphology (geometric shape) and kinetics (temporal enhancement) and pose a problem to lesion detection and classification. Their strong phenotypic differences can be visualized by MRI. Radiomics...
Conference Paper
Glioma-derived cancer stem cells (GSCs) are tumor-initiating cells and may be refractory to radiation and chemotherapy and thus have important implications for tumor biology and therapeutics. The analysis and interpretation of large proteomic data sets requires the development of new data mining and visualization approaches. Traditional techniques...
Article
Full-text available
Clinical/methodical issue: Magnetic resonance imaging (MRI) of the breast is an indispensable tool in breast imaging for many indications. Several functional parameters with MRI and positron emission tomography (PET) have been assessed for imaging of breast tumors and their combined application is defined as multiparametric imaging. Available data...
Conference Paper
Image processing can be considered as signal processing in two dimensions (2D). Filtering is one of the basic image processing operation. Filtering in frequency domain is computationally faster when compared to the corresponding spatial domain operation as the complex convolution process is modified as multiplication in frequency domain. The popula...
Conference Paper
Full-text available
HEVC/H.265 is the most interesting and cutting-edge topic in the world of digital video compression, allowing to reduce by half the required bandwidth in comparison with the previous H.264 standard. Telemedicine services and in general any medical video application can benefit from the video encoding advances. However, the HEVC is computationally e...
Conference Paper
The emphasis of this project lies in the development and evaluation of new robust and high fidelity fetal electrocardiogram (FECG) systems to determine the fetal heart rate (FHR). Recently several powerful algorithms have been suggested to improve the FECG fidelity. Until now it is unknown if these algorithms allow a real-time processing, can be us...
Article
Full-text available
PurposeTo evaluate the inter-/intra-observer agreement of BI-RADS-based subjective visual estimation of the amount of fibroglandular tissue (FGT) with magnetic resonance imaging (MRI), and to investigate whether FGT assessment benefits from an automated, observer-independent, quantitative MRI measurement by comparing both approaches. Materials and...
Conference Paper
Brain imaging studies identified brain networks that play a key role in nicotine dependence-related behavior. Functional connectivity of the brain is dynamic; it changes over time due to different causes such as learning, or quitting a habit. Functional connectivity analysis is useful in discovering and comparing patterns between functional magneti...
Conference Paper
Prostate cancer is reported to be the second most frequently diagnosed cancer of men in the world. In practise, diagnosis can be affected by multiple factors which reduces the chance to detect the potential lesions. In the last decades, new imaging techniques mainly based on MRI are developed in conjunction with Computer-Aided Diagnosis (CAD) syste...
Conference Paper
In the field of transcriptomics data the automated inference of predictive gene regulatory networks from high-throughput data is a common approach for the identification of novel genes with potential therapeutic value. Sophisticated methods have been developed that extensively make use of diverse sources of prior-knowledge to obtain biologically re...