Z. Benyo

A common periodic table of codons and amino acids.

A periodic table of codons has been designed where the codons are in regular locations. The table has four fields (16 places in each) one with each of the four nucleotides (A, U, G, C) in the central codon position. Thus, AAA (lysine), UUU (phenylalanine), GGG (glycine), and CCC (proline) were placed into the corners of the fields as the main codons (and amino acids) of the fields. They were connected to each other by six axes. The resulting nucleic acid periodic table showed perfect axial symmetry for codons. The corresponding amino acid table also displaced periodicity regarding the biochemical properties (charge and hydropathy) of the 20 amino acids and the position of the stop signals. The table emphasizes the importance of the central nucleotide in the codons and predicts that purines control the charge while pyrimidines determine the polarity of the amino acids. This prediction was experimentally tested.

Acoustic analysis of the infant cry: classical and new methods

In the last few decades many papers have written about the analysis of the infant cry. The acoustic analysis has a shorter history than emotional, physiological, etc. investigations. This paper deals with classical and new methods of acoustic analysis of the infant cry. The final goal is to detect hearing disorders according to the crying at the earliest possible moment. Classical acoustic methods were reproduced and compared with solutions, which were not available before. This paper most of all deals with the characteristics of the fundamental frequency of the cry in the time and in the frequency domain.

Future Trends in Robotic Neurosurgery

Computer Integrated Surgery has only existed for two decades, however it has already spread out world wide, with well over 100.000 operations performed. In the near future, newly developed robotic systems may conquer even the most challenging fields—such as neurosurgery—to provide better patient care and medical outcome. This paper presents the major systems and different strategies applied in robotic neurosurgery. Besides appropriate design, adequate control strategies are required to ensure maximal safety. This makes automated neurosurgery a technologically challenging area for researchers. It is also important during the design phase to consider market aspects. We anticipate that the future trends of clinical applications are outlined by the current leading research directions. The conclusions of the past years of innovation will lead forward on the path of further improvement.

Adaptive wavelet-transform-based ECG waveforms detection

A Wavelet-transform-based diverse ECG waveform detection method is presented. An adaptive structure of the processing algorithm can significantly increase the recognition ratio. As a first step, the program will correctly determine the position of QRS complexes and will separate the normal and abnormal beats. Our method allows us to modify in real time the mother-wavelet function, and in this way can be customized to an individual subject or specific waveforms. A parametrical model determines the best performing function for a specific waveform. We used our measurements, but for an adequate comparison with other processing algorithms, tests have been made for the commonly used MIT-BIH database, too. To allow greater waveform diversity we also used our measurements. QRS detection rate was above 99.9%, and for other waveforms the method performs quite well too. The negative influence of various noise types, like 50/60 Hz power line, abrupt baseline shift or drift, and low sampling rate in most cases was almost completely eliminated.

Patient monitoring on industry standard fieldbus

Currently approved medical communication standards exist only for the higher level of medical care, and not for low level communication between bed side measurement and diagnostic devices of patient monitoring systems. Our system is a new approach. Using a vendor-independent, open, broadly supported industrial fieldbus in the medical area makes possible to interconnect bed side devices via a simple two wire cable at an economical cost. The main goal in the system is to demonstrate the benefits of open system design, support the connection of existing medical devices to the fieldbus system and allowing the further extension for integration into the hospital information system (HIS) and telemedicine (telemonitoring) applications.

RECOGNITION OF VARIOUS EVENTS FROM 3-D HEART MODEL

Abstract This paper presents a new way to solve the inverse problem of electrocardiography in terms of heart model parameters. The developed event estimation and recognition method is based on an optimization system of heart model parameters. An ANN-based preliminary ECG analyser system has been created to reduce the searching space of the optimization algorithm. The optimal model parameters were determined by minimizing the objective functions, as relations of the observed and model-generated body surface ECGs. The final evaluation results, validated by physicians were about 86% correct. Starting from the fact that input ECGs contained various malfunction cases, such as Wolff-Parkinson-White (WPW) syndrome, atrial and ventricular fibrillation, these results suggest that this approach provides a robust inverse solution, circumventing most of the difficulties of the ECG inverse problem.

Stochastic approach to error estimation for image-guided robotic systems

Image-guided surgical systems and surgical robots are primarily developed to provide patient safety through increased precision and minimal invasiveness. Even more, robotic devices should allow for refined treatments that are not possible by other means. It is crucial to determine the accuracy of a system, to define the expected overall task execution error. A major step toward this aim is to quantitatively analyze the effect of registration and tracking—series of multiplication of erroneous homogeneous transformations. First, the currently used models and algorithms are introduced along with their limitations, and a new, probability distribution based method is described. The new approach has several advantages, as it was demonstrated in our simulations. Primarily, it determines the full 6 degree of freedom accuracy of the point of interest, allowing for the more accurate use of advanced application-oriented concepts, such as Virtual Fixtures. On the other hand, it becomes feasible to consider different surgical scenarios with varying weighting factors.

Automated Medical Image Processing Methods for Virtual Endoscopy

Traditional endoscopes penetrate the human body in order to provide high-resolution internal views of cavities and hollow organs. Even though such examinations are mostly considered non-invasive, the procedure causes pain, or at least discomforts the patient, who consequently needs some kind of sedation or anesthesia. Virtual endoscopes provide internal views of the human body without penetrating it, based on a set of parallel cross-sections produced with any computer tomography method. This paper presents the design and implementation of a software system, which acts like a virtual endoscope. It takes into account the general requirements of the system, gives a solution that uses a multi-step algorithm, and finally shows the resulting 3-D images. Most of the algorithmic steps have several possible solutions. Some comparisons are made among them where appropriate. Our virtual endoscope establishes 3-D internal views based on sets of 2-D slices, which originate from magnetic resonance imaging devices. The chain of the applied image processing methods consists of the followings: (1) Adaptive filtering to eliminate the low-frequency intensity non-uniformity (INU) artifact, and high-frequency “salt-and-pepper” disturbances; (2) Segmentation of the stack of MRI slices using an enhanced fuzzy C-means algorithm; (3) 3-D surface recovery algorithm based on level set methods and fast marching methods, a comparison is made between their performances; (4) Interactive visualization using modern computer graphics technologies, providing the possibility to measure distances, areas, volumes as well. The quality of service provided by the chosen method mainly depends on the resolution of the input images.

RISK ESTIMATION TECHNIQUES IN CASE OF WPW SYNDROME

Abstract This paper presents a new non-invasive method to estimate the danger to which are exposed the patients suffering from Wolff-Parkinson-White (WPW) syndrome. Our aim is to provide reliable risk estimation, and to formulate its limitations. The first task is the localization of the accessory pathway (AcP), which we solved using the stepwise Arruda algorithm. After getting the AcP location it was possible to determine the pre-excitation time and rate. A total of 42 patients were studied, and an 88% localization performance was reached. This was considered quite good result compared with the highest published figures (90%) by Boersma in 2002. The highest pre-excitation time was 92±5ms at a heart rate (HR=70±10). Although we could not measure the repolarization time of the AcP, the obtained results can help to construct non-invasive patient risk estimation.

Brain image segmentation for virtual endoscopy

This work presents an algorithm for fuzzy segmentation of MR brain images. Starting from the standard FCM and its bias-corrected version BCFCM algorithm, by splitting up the two major steps of the latter, and by introducing a new factor /spl gamma/, the amount of required calculations is considerably reduced. The algorithm provides good-quality segmented 2-D brain slices a very quick way, which makes it an excellent tool to support a virtual brain endoscope.