Konstantina S. Nikita

Automatic retinal image registration scheme using global optimization techniques

Retinal image registration is commonly required in order to combine the complementary information in different retinal modalities. In this paper, a new automatic scheme to register retinal images is presented and is currently tested in a clinical environment. The scheme considers the suitability and efficiency of different image transformation models and function optimization techniques, following an initial preprocessing stage. Three different transformation models-affine, bilinear and projective-as well as three optimization techniques-downhill simplex method, simulated annealing and genetic algorithms-are investigated and compared in terms of accuracy and efficiency. The registration of 26 pairs of fluoroscein angiography and indocyanine green chorioangiography images with the corresponding red-free retinal images, showed the superiority of combining genetic algorithms with the affine and bilinear transformation models. A comparative study of the proposed automatic registration scheme against the manual method, commonly used in clinical practice, is finally presented showing the advantage of the proposed automatic scheme in terms of accuracy and consistency.

A Review of Implantable Patch Antennas for Biomedical Telemetry: Challenges and Solutions [Wireless Corner]

Biomedical telemetry permits the transmission (telemetering) of physiological signals at a distance. One of its latest developments is in the field of implantable medical devices (IMDs). Patch antennas currently are receiving significant scientific interest for integration into the implantable medical devices and radio-frequency (RF)-enabled biotelemetry, because of their high flexibility in design, conformability, and shape. The design of implantable patch antennas has gained considerable attention for dealing with issues related to biocompatibility, miniaturization, patient safety, improved quality of communication with exterior monitoring/control equipment, and insensitivity to detuning. Numerical and experimental investigations for implantable patch antennas are also highly intriguing. The objective of this paper is to provide an overview of these challenges, and discuss the ways in which they have been dealt with so far in the literature.

Miniature Scalp-Implantable Antennas for Telemetry in the MICS and ISM Bands: Design, Safety Considerations and Link Budget Analysis

We study the design and radiation performance of novel miniature antennas for integration in head-implanted medical devices operating in the MICS (402.0-405.0 MHz) and ISM (433.1-434.8, 868.0-868.6 and 902.8-928.0 MHz) bands. A parametric model of a skin-implantable antenna is proposed, and a prototype is fabricated and tested. To speed-up antenna design, a two-step methodology is suggested. This involves approximate antenna design inside a simplified geometry and further Quasi-Newton optimization inside a canonical model of the intended implantation site. Antennas are further analyzed inside an anatomical human head model. Results indicate strong dependence of the exhibited radiation performance (radiation pattern, gain, specific absorption rate and quality of communication with exterior equipment) on design parameters and operation frequency. The study provides valuable insight into the design of implantable antennas, addressing the suitability of canonical against anatomical tissue models for design purposes, and assessing patient safety and link budget at various frequencies. Finite Element and Finite Difference Time Domain numerical solvers are used at different stages of the antenna design and analysis procedures to suit specific needs. The proposed design methodology can be applied to optimize antennas for several implantation scenarios and biotelemetry applications.

A Real Time Simulation Model of Glucose-Insulin Metabolism for Type 1 Diabetes Patients

In this paper, a simulation model of glucose-insulin metabolism for Type 1 diabetes patients is presented. The proposed system is based on the combination of compartmental models (CMs) and artificial neural networks (NNs). This model aims at the development of an accurate system, in order to assist Type 1 diabetes patients to handle their blood glucose profile and recognize dangerous metabolic states. Data from a Type 1 diabetes patient, stored in a database, have been used as input to the hybrid system. The data contain information about measured blood glucose levels, insulin intake, and description of food intake, along with the corresponding time. The data are passed to three separate CMs, which produce estimations about (i) the effect of short acting (SA) insulin intake on blood insulin concentration, (ii) the effect of intermediate acting (IA) insulin intake on blood insulin concentration, and (iii) the effect of carbohydrate intake on blood glucose absorption from the gut. The outputs of the three CMs are passed to a recurrent NN (RNN) in order to predict subsequent blood glucose levels. The RNN is trained with the real time recurrent learning (RTRL) algorithm. The resulted blood glucose predictions are promising for the use of the proposed model for blood glucose level estimation for Type 1 diabetes patients

SMARTDIAB: A Communication and Information Technology Approach for the Intelligent Monitoring, Management and Follow-up of Type 1 Diabetes Patients

SMARTDIAB is a platform designed to support the monitoring, management, and treatment of patients with type 1 diabetes mellitus (T1DM), by combining state-of-the-art approaches in the fields of database (DB) technologies, communications, simulation algorithms, and data mining. SMARTDIAB consists mainly of two units: 1) the patient unit (PU); and 2) the patient management unit (PMU), which communicate with each other for data exchange. The PMU can be accessed by the PU through the internet using devices, such as PCs/laptops with direct internet access or mobile phones via a Wi-Fi/General Packet Radio Service access network. The PU consists of an insulin pump for subcutaneous insulin infusion to the patient and a continuous glucose measurement system. The aforementioned devices running a user-friendly application gather patients related information and transmit it to the PMU. The PMU consists of a diabetes data management system (DDMS), a decision support system (DSS) that provides risk assessment for long-term diabetes complications, and an insulin infusion advisory system (IIAS), which reside on a Web server. The DDMS can be accessed from both medical personnel and patients, with appropriate security access rights and front-end interfaces. The DDMS, apart from being used for data storage/retrieval, provides also advanced tools for the intelligent processing of the patients data, supporting the physician in decision making, regarding the patients treatment. The IIAS is used to close the loop between the insulin pump and the continuous glucose monitoring system, by providing the pump with the appropriate insulin infusion rate in order to keep the patients glucose levels within predefined limits. The pilot version of the SMARTDIAB has already been implemented, while the platforms evaluation in clinical environment is being in progress.

Comparison of Multiresolution Features for Texture Classification of Carotid Atherosclerosis From B-Mode Ultrasound

In this paper, a multiresolution approach is suggested for texture classification of atherosclerotic tissue from B-mode ultrasound. Four decomposition schemes, namely, the discrete wavelet transform, the stationary wavelet transform, wavelet packets (WP), and Gabor transform (GT), as well as several basis functions, were investigated in terms of their ability to discriminate between symptomatic and asymptomatic cases. The mean and standard deviation of the detail subimages produced for each decomposition scheme were used as texture features. Feature selection included 1) ranking the features in terms of their divergence values and 2) appropriately thresholding by a nonlinear correlation coefficient. The selected features were subsequently input into two classifiers using support vector machines (SVM) and probabilistic neural networks. WP analysis and the coiflet 1 produced the highest overall classification performance (90% for diastole and 75% for systole) using SVM. This might reflect WPs ability to reveal differences in different frequency bands, and therefore, characterize efficiently the atheromatous tissue. An interesting finding was that the dominant texture features exhibited horizontal directionality, suggesting that texture analysis may be affected by biomechanical factors (plaque strains).

Study of the coupling between human head and cellular phone helical antennas

The interaction between normal-mode helical antennas and human head models is analyzed, using both a novel accurate semi-analytical method and finite-difference time-domain (FDTD) simulations. The semi-analytical method is based on the combination of Greens functions theory with the method of moments (Green/MoM) and is able to model arbitrarily shaped wire antennas radiating in the close proximity of layered lossy dielectric spheres representing simplified models of the human head. The purpose of the development of the Green/MoM technique is to provide a reliable tool for preliminary (worst case) estimation of human head exposure to the field generated by different antenna configurations with emphasis on the helical antenna, representing the most diffused antenna type used in modern cellular handsets. Furthermore, the accurate semi-analytical character of the Green/MoM technique permits the accuracy assessment of purely numerical techniques, such as the FDTD, which is currently the most widely used computational method in mobile communication dosimetric problems, since it allows modeling of anatomically based head models. After appropriate benchmarking, FDTD simulations are used to study the interaction between a heterogeneous anatomically correct model of the human head exposed to a normal-mode helix monopole operating at 1710 MHz mounted on the top of a metal box representing a realistic mobile communication terminal. The study of both canonical and realistic exposure problems includes computations of specific absorption rates (SARs) inside the human head, total power absorbed by the head and assessment of antenna performance. Emphasis is placed on the comparative dosimetric assessment between adults and children head models.

In silico radiation oncology: combining novel simulation algorithms with current visualization techniques

The concept of in silica radiation oncology is clarified in this paper. A brief literature review points out the principal domains in which experimental, mathematical, and three-dimensional (3-D) computer simulation models of tumor growth and response to radiation therapy have been developed. Two paradigms of 3-D simulation models developed by our research group are concisely presented. The first one refers to the in vitro development and radiation response of a tumor spheroid whereas the second one refers to the fractionated radiation response of a clinical tumor in vivo based on the patients imaging data. In each case, a description of the salient points of the corresponding algorithms and the visualization techniques used takes place. Specific applications of the models to experimental and clinical cases are described and the behavior of the models is two- and three-dimensionally visualized by using virtual reality techniques. Good qualitative agreement with experimental and clinical observations strengthens the applicability of the models to real situations. A protocol for further testing and adaptation is outlined. Therefore, an advanced integrated patient specific decision support and spatio-temporal treatment planning system is expected to emerge after the completion of the necessary experimental tests and clinical evaluation.

Performance of a novel miniature antenna implanted in the human head for wireless biotelemetry

In this study, we present a novel, miniaturized, biocompatible antenna at the medical implant communications service (MICS) band (402–405 MHz) for integration in wireless biotelemetry devices implanted in the human head. To reduce simulation time, the antenna is designed while in the center of a skin tissue simulating box and subsequently implanted inside the skin tissue of an anatomical human head model. The resonance, radiation and specific absorption rate (SAR) performance of the antenna is evaluated and design modifications are suggested to overcome the inherent detuning effect.

Analysis of the interaction between a layered spherical human head model and a finite-length dipole

The coupling between a finite-length dipole antenna and a three-layer lossy dielectric sphere, representing a simplified model of the human head, is analyzed theoretically in this paper. The proposed technique is based on the theory of Greens functions in conjunction with the method of auxiliary sources (MAS). The Greens function of the three-layer sphere can be calculated as the response of this object to the excitation generated by an elementary dipole of unit dipole moment. The MAS is then applied to model the dipole antenna by distributing a set of auxiliary current sources on a virtual surface lying inside the antenna physical surface. By imposing appropriate boundary conditions at a finite number of points on the real surface of the antenna, the unknown auxiliary sources coefficients can be calculated and, hence, the electric field at any point in space can be easily obtained. Numerical results concerning the specific absorption rate inside the head, the total power absorbed by the head, the input impedance, and the radiation pattern of the antenna are presented for homogeneous and layered head models exposed to the near-field radiation of half-wavelength dipoles at 900 and 1710 MHz. The developed method can serve as a reliable platform for the assessment of purely numerical electromagnetic methods. The method can also provide an efficient tool for accurate testing and comparison of different antenna designs since generalizations required to treat more complex antenna configurations are straightforward.