Laszlo Szilagyi

Laszlo Szilagyi
Sapientia Hungarian University of Transylvania · Department of Electrical Engineering

PhD habil

About

178
Publications
15,057
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1,431
Citations
Citations since 2016
56 Research Items
841 Citations
2016201720182019202020212022050100150
2016201720182019202020212022050100150
2016201720182019202020212022050100150
2016201720182019202020212022050100150

Publications

Publications (178)
Article
Full-text available
Non-coordinated physical activity may lead to hypoglycemia, which is a dangerous condition for diabetic people. Decision support systems related to type 1 diabetes mellitus (T1DM) still lack the capability of automated therapy modification by recognizing and categorizing the physical activity. Further, this desired adaptive therapy should be achiev...
Article
The objective and automated detection of pneumonia represents a serious challenge in medical imaging, because the signs of the illness are not obvious in CT or X-ray scans. Further on, it is also an important task, since millions of people die of pneumonia every year. The main goal of this paper is to propose a solution for the above mentioned prob...
Article
Full-text available
The ability of healthcare workers to learn proper hand hygiene has been an understudied area of research. Generally, hand hygiene skills are regarded as a key contributor to reduce critical infections and healthcare-associated infections. In a clinical setup, at a Neonatal Intensive Care Unit (NICU), the outcome of a multi-modal training initiative...
Article
Full-text available
Real-time multilingual phrase detection from/during online video presentations—to support instant remote diagnostics—requires near real-time visual (textual) object detection and preprocessing for further analysis. Connecting remote specialists and sharing specific ideas is most effective using the native language. The main objective of this paper...
Article
Full-text available
Automatic brain tumor segmentation from multimodal MRI plays a significant role in assisting the diagnosis, treatment, and surgery of glioblastoma and lower glade glioma. In this article, we propose applying several deep learning techniques implemented in AWS SageMaker Framework. The different CNN architectures are adapted and fine-tuned for our pu...
Article
Full-text available
The accurate and reliable segmentation of gliomas from magnetic resonance image (MRI) data has an important role in diagnosis, intervention planning, and monitoring the tumor’s evolution during and after therapy. Segmentation has serious anatomical obstacles like the great variety of the tumor’s location, size, shape, and appearance and the modifie...
Conference Paper
Full-text available
In the case of diabetes mellitus physical activity does have a high effect on the glycemic state of the patients. This is especially regarding the patients with Type 1 diabetes mellitus, who need external insulin administration in their daily life. Nevertheless, physical activity - as one source of stress - is underrepresented in the decisions of p...
Article
Full-text available
Suppressed fuzzy c-means clustering was proposed as an attempt to combine the better properties of hard and fuzzy c-means clustering, namely the quicker convergence of the former and the finer partition quality of the latter. In the meantime, it became much more than that. Its competitive behavior was revealed, based on which it received two genera...
Chapter
Card counting is a family of casino card game advantage gambling strategies, in which a player keeps a mental tally of the cards played in order to calculate whether the next hand is likely to be in the favor of the player or the dealer. A card counting system assigns point values (weights) to the cards. Summing the point values of the already play...
Chapter
The development of brain tumor segmentation techniques based on multi-spectral MR image data has relevant impact on the clinical practice via better diagnosis, radiotherapy planning and follow-up studies. This task is also very challenging due to the great variety of tumor appearances, the presence of several noise effects, and the differences in s...
Chapter
In this paper, we experiment with methods for obtaining binary sequences with a random probability mass function and with low autocorrelation and use it to generate ambiguous outcomes. Outputs from a neural network are mixed and shuffled, resulting in binary sequences whose probability mass function is non-convergent, constantly moving and changing...
Chapter
Absolute values in magnetic resonance image data do not say anything about the investigated tissues. All these numerical values are relative, they depend on the imaging device and they may vary from session to session. Consequently, there is a need for histogram normalization before any other processing is performed on MRI data. The Brain Tumor Seg...
Chapter
The number of medical imaging devices is quickly and steadily rising, generating an increasing amount of image records day by day. The number of qualified human experts able to handle this data cannot follow this trend, so there is a strong need to develop reliable automatic segmentation and decision support algorithms. The Brain Tumor Segmentation...
Article
Full-text available
According to WHO estimates, 400 million people suffer from diabetes, and this number is likely to double by year 2030. Unfortunately, diabetes can have severe complications like glaucoma or retinopathy, which both can cause blindness. The main goal of our research is to provide an automated procedure that can detect retinopathy-related lesions of t...
Chapter
In this paper a palm vein identification system is presented, which exploits the strength of convolutional neural network (CNN) architectures. We built and compared six different CNN approaches for biometric identification based on palm images. Four of them were developed by applying transfer learning and fine-tuning techniques to relevant deep lea...
Conference Paper
Accuracy is the most important quality marker in medical image segmentation. However, when the task is to handle large volumes of data, the relevance of processing speed rises. In machine learning solutions the optimization of the feature set can significantly reduce the computational load. This paper presents a method for feature selection and app...
Preprint
Full-text available
Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions...
Article
Full-text available
Several hundreds of thousand humans are diagnosed with brain cancer every year, and the majority dies within the next two years. The chances of survival could be easiest improved by early diagnosis. This is why there is a strong need for reliable algorithms that can detect the presence of gliomas in their early stage. While an automatic tumor detec...
Chapter
In this paper we present a biometric system based on dorsal hand vein recognition. The preprocessing steps are tuned for image similar or captured with the same scanner as used for the creation of NCUT database. Image quality was improved according to the segmentation method applied. A coarse segmentation technique based on ordinal image encoding h...
Chapter
The development of automatic tumor detection and segmentation procedures enables the computers to preprocess huge sets of MRI records and draw the attention of medical staff upon suspected positive cases. This paper proposes a machine learning solution based on binary decision trees and random forest technique, trained to provide accurate segmentat...
Article
The valve-sparing aortic root surgery is a common treatment of several aortic diseases. Although, the aortic valves are generally fixed in an even distribution during these operations, recently developed special tools enable the back-sewing of the valves in the original, patient specific distribution that likely provides better hemodynamic function...
Article
Full-text available
Early repolarization pattern (ERP), a form of J-wave syndromes, was considered long time a benign ECG phenomenon. However, recent data confirmed that certain phenotypes of ERP are related to an increased risk of sudden cardiac death (idiopathic ventricular fibrillation). Our paper gives a short and practical update regarding the main issues related...
Article
Introduction: Hand hygiene is probably the most effective tool of nosocomial infection prevention, however, proper feedback and control is needed to develop the individual hand hygiene practice. Aim: Assessing the efficiency of modern education tools, and digital demonstration and verification equipment during their wide-range deployment. Metho...
Article
Ultraviolet spectrum markers are widely used for hand hygiene quality assessment, although their microbiological validation has not been established. A microbiology-based assessment of the procedure was conducted. Twenty-five artificial hand models underwent initial full contamination, then disinfection with UV-dyed hand rub solution, digital imagi...
Article
Full-text available
Objective. The possible effect of blood pressure measurements per se on heart rate variability (HRV) was studied in the setting of concomitant ambulatory blood pressure monitoring (ABPM) and Holter ECG monitoring (HM). Methods. In 25 hypertensive patients (14 women and 11 men, mean age: 58.1 years), 24-hour combined ABPM and HM were performed. For...
Article
Full-text available
Coronary artery disease represents one of the leading reasons of death worldwide, and acute coronary syndromes are their most devastating consequences. It is extremely important to identify the patients at risk for developing an acute myocardial infarction, and this goal can be achieved using noninvasive imaging techniques. Coronary computed tomogr...
Chapter
One of the main challenges in the field of clustering is creating algorithms that are both accurate and robust. The fuzzy-possibilistic product partition c-means clustering algorithm was introduced with the main goal of producing accurate partitions in the presence of outlier data. This chapter presents several clustering algorithms based on the fu...
Conference Paper
In this article we propose and tune a discriminative model based on Random Forest (RF) to accomplish brain tumor segmentation in multimodal MR images. The objective of tuning is to establish the optimal parameter values and the most significant constraints of the dis-criminative model. During the building of the RF classifier, the algorithm evaluat...
Conference Paper
Detecting clusters of different sizes represents a serious difficulty for all c-means clustering models. This study investigates the set of various modified fuzzy c-means clustering algorithms within the bounds of the probabilistic constraint, from the point of view of their sensitivity to cluster sizes. Two numerical frameworks are constructed, on...
Conference Paper
This comparative study employs several modified versions of the fuzzy c-means algorithm in image color reduction, with the aim of assessing their accuracy and efficiency. To assure equal chances for all algorithms, a common framework was established that preprocesses input images in terms of a preliminary color quantization, extraction of histogram...
Conference Paper
Early detection is the key of success in the treatment of tumors. Establishing methods that can identify the presence and position of tumors in their early stage is a current great challenge in medical imaging. This study proposes a machine learning solution based on binary decision trees and random forest technique, aiming at the detection and acc...
Article
Background: Graph-based hierarchical clustering algorithms become prohibitively costly in both execution time and storage space, as the number of nodes approaches the order of millions. Objective: A fast and highly memory efficient Markov clustering algorithm is proposed to perform the classification of huge sparse networks using an ordinary per...
Article
The aim of this study was to objectively assess the hand hygiene performance of medical students. Hand rubbing technique was evaluated by employing innovative UV-light-based imaging technology, identifying patterns and trends in missed areas after applying WHO's six-step protocol. This specially designed hand hygiene education and assessment progra...
Article
Full-text available
Objective . The aim of this study is to define the normal range for average real variability (ARV) and to establish whether it can be considered as an additional cardiovascular risk factor. Methods . In this observational study, 110 treated hypertensive patients were included and admitted for antihypertensive treatment adjustment. Circadian blood p...
Conference Paper
A novel concept of intelligence called “societal intelligence” and its related architecture for solving complex problems are introduced. The idea is based on what we consider on the “intelligence of human society”. For illustrative purposes, a case study is realized, which involves the solution of a difficult problem in a societal multi-agent syste...
Conference Paper
The aim of this study was to establish a multi-stage fuzzy c-means (FCM) framework for the automatic and accurate detection of brain tumors from multimodal 3D magnetic resonance image data. The proposed algorithm uses prior information at two points of the execution: (1) the clusters of voxels produced by FCM are classified as possibly tumorous and...
Conference Paper
While empirical evidence suggest that the brain can represent and operate on probability distributions, it is not clear how multivariate dependencies can be detected and represented by neural circuits. Based on previous work and the principle of entropy distillation, the paper introduces a massively parallel connectionist machine whose spiking beha...
Conference Paper
A fast and highly memory-efficient implementation of the TRIBE-MCL clustering algorithm is proposed to perform the classification of huge protein sequence data sets using an ordinary PC. Improvements compared to previous versions are achieved through adequately chosen data structures that facilitate the efficient handling of symmetric sparse matric...
Conference Paper
This paper attempts to unify the theory of a certain class of modified variants and another class of manipulated versions of the fuzzy c-means algorithm. Starting from the objective function of the so-called fuzzy c-means algorithm with generalized improved partition (GIFP-FCM), and defining its rewarding term in a more flexible way, we obtain a un...
Article
This study investigated the effectiveness of targeting hand hygiene technique using a new training device that provides objective, personal and quantitative feedback. One hundred and thirty-six healthcare workers in three Hungarian hospitals participated in a repetitive hand hygiene technique assessment study. Ultraviolet (UV)-labelled hand rub was...
Article
Full-text available
This paper introduces a Petri net designed for the simulation of the ancient game called Rock-Paper-Scissors or Roshambo. The network enables us to simulate the behavior of machine players and allows us to design and evaluate strategies against weighted random machine opponents. The paper also presents a theoretical calculus on winning chances. Sim...
Article
Blind Speaker Clustering is a task within speech technology, where we have a collection of speech recordings (utterances), and the goal is to identify which utterances belong to the same speakers. To aid the clustering process in this task, we performed pre-processing steps such as feature selection and Principal Component Analysis (PCA); still, th...
Conference Paper
In this paper we propose a quick and memory-efficient implementation of the TRIBE-MCL clustering algorithm, suitable for accurate classification of large-scale protein sequence data sets. A symmetric sparse matrix structure is introduced that can efficiently handle most operations of the main loop. The reduction of memory requirements is achieved b...
Conference Paper
Diabetes mellitus is a serious chronic condition of the human metabolism. The development of an automated treatment has reached clinical phase in the last few years. The goal is to keep the blood glucose concentration within a certain region with minimal interaction required by the patient or medical personnel. However, there are still several prac...
Conference Paper
Recent achievements in graph-based clustering algorithms revealed the need for large-scale test data sets. This paper introduces a procedure that can provide synthetic but realistic test data to the hierarchical Markov clustering algorithm. Being created according to the structure and properties of the SCOP95 protein sequence data set, the syntheti...
Conference Paper
Creating accurate and robust clustering models is utmost important in pattern recognition. This paper introduces an elliptic shell clustering model aiming at accurate detection of ellipsoids in the presence of outlier data. The proposed fuzzy-possibilistic product partition c-elliptical shell algorithm (FP3CES) combines the probabilistic and possib...
Article
This paper provides a comparative study of several enhanced versions of the fuzzy c-means clustering algorithm in an application of histogram-based image color reduction. A common preprocessing is performed before clustering, consisting of a preliminary color quantization, histogram extraction and selection of frequently occurring colors of the ima...
Article
Full-text available
Hypertension in the elderly is characterized by isolated systolic hypertension and high variability, but its clinical significance is not yet fully understood. The goal of this paper was to assess circadian blood pressure variability (BPV) in elderly hypertensives, and to determine its relationship to cardiovascular risk factors. To achieve this go...
Article
In this paper we propose an efficient color reduction framework that employs c-means clustering to extract optimal colors. The processing consists of three stages: preprocessing, c-means clustering, and creation of the output image. The main goal of the first stage is to transform the pixel matrix into a list of records, which indicates what colors...
Article
Intending to achieve an algorithm characterized by the quick convergence of hard c-means (HCM) and finer partitions of fuzzy c-means (FCM), suppressed fuzzy c-means (s-FCM) clustering was designed to augment the gap between high and low values of the fuzzy membership functions. Suppression is produced via modifying the FCM iteration by creating a c...
Article
TRIBE-MCL is a Markov clustering algorithm that operates on a graph built from pairwise similarity information of the input data. Edge weights stored in the stochastic similarity matrix are alternately fed to the two main operations, inflation and expansion, and are normalized in each main loop to maintain the probabilistic constraint. In this pape...
Article
The fuzzy local information c-means (FLICM) algorithm, introduced by Krinidis and Chatzis (2010), was designed to perform highly accurate segmentation of images contaminated with high-frequency noise. This algorithm includes an extra additive term to the objective function of the fuzzy c-means (FCM), called local descriptor fuzzy factor, allowing t...
Conference Paper
Two efficient versions of a Markov clustering algorithm are proposed, suitable for fast and accurate grouping of protein sequences. First, the essence of the matrix splitting approach consists in optimal reordering of rows and columns in the similarity matrix after every iteration, transforming it into a matrix with several compact blocks along the...
Conference Paper
This study focuses on the effects of artificial cardiac tissue in the excitation-contraction process of the ventricular muscle. We developed a spatio-temporal computerized model of the whole heart that handles half millimeter sized compartments using 1 microsecond time step. We employed the effect of muscle fiber direction, laminar sheets, depolari...
Article
In this paper we propose an efficient reformulation of a Markov clustering algorithm, suitable for fast and accurate grouping of protein sequences, based on pairwise similarity information. The proposed modification consists of optimal reordering of rows and columns in the similarity matrix after every iteration, transforming it into a matrix with...
Article
One of the main challenges in the field of clustering is creating algorithms that are both accurate and robust. This paper introduces a novel fuzzy-possibilistic shell clustering model aiming at accurate detection of circles, spheres, and multidimensional spheroids in the presence of outlier data. The proposed fuzzy-possibilistic product partition...
Article
Full-text available
BACKGROUND: and hygiene compliance is generally assessed by observation of adherence to the "WHO five moments" using numbers of opportunities as the denominator. The quality of the activity is usually not monitored since there is no established methodology for the routine assessment of hand hygiene technique. The aim of this study was to objectivel...
Conference Paper
Aims: In the focus of this study stand the fibroblast cells that under physiological terms are providing structural support for the heart, but under patho-physiological conditions they can obstruct the pacemaker activity and the excitation spread function of the heart that may develop arrhythmia.
Conference Paper
Aims: This study is aimed to present the simulation of several types of cardiac arrhythmias using adaptively selected spatio-temporal resolution, involving the accuracy analysis of the experiment.
Article
Intensity inhomogeneity or intensity non-uniformity (INU) is an undesired phenomenon that represents the main obstacle for magnetic resonance (MR) image segmentation and registration methods. Various techniques have been proposed to eliminate or compensate the INU, most of which are embedded into classification or clustering algorithms, they genera...
Conference Paper
Aims: The goal of this study is to assess the influence of the accessory pathway's (AcP) location and its repolarization period on the incidence of ventricular fibrillation (VF), in order to develop a non-invasive method able to select the most endangered patients that suffer from Wolff-Parkinson-White (WPW) syndrome. Methods: 12-lead ECG was recor...
Conference Paper
Aims: This study focuses on the most important cardiac malfunction cases responsible for sudden cardiac death and on detailed visualization of all formation phases of the deadly, self maintaining spiral waves (SW) that may occur in the ventricular tissue and develop ventricular fibrillation (VF). Methods: We developed a spatio-temporal computerized...
Conference Paper
This study is aimed to present the development phases of hypoxia and anoxia using the dynamic Luo-Rudy II (LR) ventricular cell model. This task involves the robustness analysis of the selected cell model in low oxygen level circumstances that alter the ionic conductance properties of the cellular membrane and partially or totally inhibit the ionic...
Conference Paper
This paper presents a novel semi-automated image processing procedure dedicated to the identification and characterization of the dental root canal, based on high-resolution micro-CT records. After the necessary image enhancement, parallel slices are individually segmented via histogram based quick fuzzy c-means clustering. The 3D model of root can...
Conference Paper
Intensity inhomogeneity or intensity non-uniformity (INU) is an undesired phenomenon that represents the main obstacle for magnetic resonance (MR) image segmentation and registration methods. Various techniques have been proposed to eliminate or compensate the INU, most of which are embedded into clustering algorithms, and they generally have diffi...
Conference Paper
Curve skeletons are used for linear representation of 3D objects in a wide variety of engineering and medical applications. The outstandingly robust and flexible curve skeleton extraction algorithm, based on generalized potential fields, suffers from seriously heavy computational burden. In this paper we propose and evaluate a hierarchical formulat...
Conference Paper
Nosocomial infections are the undesirable result of a treatment in a hospital, or a health care service unit, not related to the patient's original condition. Despite the evolution of medicine, fundamental problems with hand hygiene remain existent, leading to the spread of nosocomial infections. Our group has been working on a generic solution to...