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X-ray fluoroscopy is a medical imaging modality that provides continuous real-time screening of patient’s organs and various radiopaque surgical objects. Fluoroscopy usually requires long and unpredictable exposure times, thus radiation intensity must be heavily reduced to limit patient’s dose. This gives rise to the well-known Poisson noise, which results in very poor image quality. Commercial fluoroscopes usually improve image quality via real-time temporal averaging, which produces motion blur in moving scenes. The Noise Variance Conditioned Average (NVCA) algorithm exploits the a priori knowledge of Poisson noise statistics to provide efficient noise reduction, while preserving the edges of moving objects. However, accurate setting of NVCA parameters is required to achieve the best results, and this could be supported by image quality assessment (IQA) indices. This study presents a novel, edge-aware IQA index, named Sensitivity of Edge Detection (SED), and compares it against the well-established Feature Similarity (FSIM) index, to assess their efficiency in determining the optimal parameters for NVCA. The preliminary results obtained in this study suggest SED could be more efficient than FSIM in identifying the best trade-off between noise reduction and edge preservation, and could be also used to determine the optimal parameters of other denoising algorithms.

Comparison of derivative operators via quantitative performance analysis is rarely addressed in medical imaging. Indeed, the main application of such operators is the extraction of edges and, since there is no unequivocal definition of edges, the common trend is to identify the best performing operator based on a qualitative match between the extracted edges and the fickle human perception of object boundaries. This study presents an objective comparison of four first-order derivative operators through quantitative analysis of results yielded in a specific task, i.e. a spine kinematics application. Such application is based on a template matching method, which estimates common kinematic parameters of intervertebral segments from an X-ray fluoroscopy sequence of spine motion, by operating on the image derivatives of each frame. Therefore, differences in image derivatives, computed via different derivative operators, may lead to differences in estimated parameters of intervertebral kinematics. The comparison presented in this study focused on the trajectory of the instantaneous center of rotation (ICR) of an intervertebral segment, as it is particularly sensitive even to very small differences in displacements and velocities. Therefore, a quantitative analysis of the discrepancies between the ICR trajectories, obtained with each of the four considered derivative operators, was carried out by defining quantitative measures. The results showed detectable differences in the obtained ICR trajectories, thus highlighting the need for quantitative analysis of derivative operator performances in applications aimed at providing quantitative results. However, the significance level of such differences for clinical applications should be further assessed, but, currently, it is not possible, as there is no consensus and sufficient data on kinematic parameters features associated with specific spinal pathologies.

This paper presents an analysis on the suitability of a low cost motion capture system to support the development of generic applications within medical scenarios. In this study we used the Microsoft Kinect (first generation) sensor as basic technology for its wide availability and the relatively low cost, which generated great interest of the scientific community in several application fields. Most of the studies found in literature however, do not address the quality and reliability of the raw data (objects position and depth) considering only the results of the integrated 3D recognition algorithms for the final skeleton/gesture analysis. This can be critical in rehabilitation, in which the knowledge of accuracy, reliability and performance in tracking patient body movements is required and assessed. To this aim, this article proposes an experimental protocol to analyze the Kinect measurement capabilities, via the definition of peculiar parameters. Here we also introduced an analysis of performance versus usage time. Results showed some weak- nesses of the sensor. Specifically, resolution was found in the range of tens of millimeters while degrading over time. The adoption of the Microsoft Kinect (first generation) in medical scenarios should therefore be considered with respect to the application it serves having clear in mind its performances and limitations.

Infantile Nystagmus Syndrome, or Congenital Nystagmus, is an ocular-motor disorder characterized by involuntary, conjugated and bilateral to and fro ocular oscillations. Good visual acuity in congenital nystagmus can be achieved during the foveation periods in which eye velocity slows down while the target image crosses the fovea. Visual acuity was found to be mainly dependent on the duration of the foveation periods. In this work a new approach is proposed for estimation of foveation parameters: a cubic spline interpolation of the nystagmus recording before localizing the start point of foveation window and to estimate its duration. The performances of the proposed algorithm were assessed in comparison with a previously developed algorithm, used here as gold standard. The obtained results suggest that the spline interpolation could be a useful tool to filter the eye movement recordings before applying an algorithm to estimate the foveation window parameters.

— Long term recording of biomedical signals such as ECG, EMG, respiration and other information (e.g. body motion) can improve diagnosis and potentially monitor the evolution of many widespread diseases. However, long term monitoring requires specific solutions, portable and wearable equipment that should be particularly comfortable for patients. The key-issues of portable biomedical instrumentation are: power consumption, long-term sensor stability, comfortable wearing and wireless connectivity. In this scenario, it would be valuable to realize prototypes using available technologies to assess long-term personal monitoring and foster new ways to provide healthcare services. The aim of this work is to discuss the advantages and the drawbacks in long term monitoring of biopotentials and body movements using textile electrodes embedded in clothes. The textile electrodes were embedded into garments; tiny shirt and short were used to acquire electrocardiographic and electromyographic signals. The garment was equipped with low power electronics for signal acquisition and data wireless transmission via Bluetooth. A small, battery powered, biopotential amplifier and three-axes acceleration body monitor was realized. Patient monitor incorporates a microcontroller, analog-to-digital signal conversion at programmable sampling frequencies. The system was able to acquire and to transmit realtime signals, within 10 m range, to any Bluetooth device (including PDA or cellular phone). The electronics were embedded in the shirt resulting comfortable to wear for patients. Small size MEMS 3-axes accelerometers were also integrated.

Cardiotocographic data provide physicians information about foetal development and, through assessment of specific parameters (like accelerations, uterine contractions, ...), permit to assess conditions such as foetal distress. An incorrect evaluation of foetal status can be of course very dangerous. In the last decades, to improve interpretation of cardiotocographic recordings, great interest has been dedicated to FHRV spectral analysis. It is worth reminding that FHR is intrinsically an uneven series and that to obtain evenly sampled series, many commercial cardiotocographs use a zero-order interpolation (storage rate of CTG data equal to 4 Hz). This is not suitable for frequency analyses because interpolation introduces alterations in the FHR power spectrum. In particular, this interpolation process can produce artifacts and an attenuation of the high-frequency components of the PSD that, for example, affects the estimation of the sympatho-vagal balance (SVB - computed as low-frequency/high-frequency ratio), which represents an important clinical parameter. In order to estimate the frequency spectrum alterations due to zero-order interpolation and other CTG storage rates, in this work, we simulated uneven FHR series with set characteristics, their evenly spaced versions (with different storage rates) and computed SVB values by PSD. For PSD estimation, we chose the Lomb method, as suggested by other authors in application to uneven HR series