Computerized automatic system to obtain inspiration/expiration chest roentgenograms without patient collaboration

Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): This publication is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 954783. Background Stereotactic arrhythmia radio-ablation (STAR) is a promising strategy for the non-invasive treatment of ventricular arrhythmias (VA). The management of the cardio-respiratory motion of the target and the reduction of the uncertainties related to patients’ positioning are two of the main challenges that STAR has to overcome. A prototype of a system was developed that can automatically acquire and interpret echocardiographic images using an artificial intelligence (AI) algorithm to calculate cardiac displacement in real-time. Purpose To evaluate the feasibility of this automatic acquisition system in patients with a history of VA. Methods We conducted a single center, feasibility study enrolling consecutive patients with a history of VA. Echocardiographic images were automatically acquired from the parasternal and apical views with a dedicated probe. The system was designed to hold the probe fixed to the chest in the supine position during both free-breathing and short expiratory breath-hold sequences, to simulate STAR treatment. The primary endpoint was the percentage of patients reaching a score ≥2 in a multi-parametric assessment evaluating the quality of automatically acquired images in terms of: A - allowing a proper identification of the cardiac cycle phase using the AI algorithm, B - allowing a correct measurement of the heart displacement by the AI algorithm, C - ability to visually distinguish typical cardiac structures, and D - stability of the image throughout the respiration cycle. Moreover, we investigated the potential impact of clinical and demographic characteristics on achieving the primary outcome. Results From May to September 2021, we enrolled 24 patients (63±14 years, 21% females). All of them had a history of VA and 21 (88%) had an ICD. Eight patients (33%) had coronary artery disease, 12 (50%) had non-ischemic cardiomyopathy, and 3 had idiopathic VA. Parasternal as well as apical images were obtained from all patients except from one, in whom parasternal view could not be collected due to the patient’s inability to maintain the supine position. The primary outcome was achieved in 23 patients (96%) for the apical view, in 20 patients (87%) for the parasternal view, and in all patients in at least one of the two views. The images quality was maximal (i.e. score=4) in at least one of the two windows in 19 patients (79%). Atrial fibrillation arrhythmia was the only clinical characteristics associated with a poor score outcome in both imaging windows (apical p=0,022, parasternal p=0,014). Conclusion An automatic ultrasonographic image acquisition system associated with an AI algorithm is feasible for real-time monitoring of cardiac motion in patients with a history of VA. The possibility of real-time, non-invasive monitoring of cardiac position would lead to a significant improvement in the quality and safety of STAR treatment, particularly in case of treatment with heavy particles such as protons and carbon ions.

An automatic microscope image acquisition, evaluation, and recognition system was developed for the analysis of Utermöhl plankton chambers in terms of taxonomic algae recognition. The system called PLASA (Plankton Structure Analysis) comprises (1) fully automatic archiving (optical fixation) of aqueous specimens as digital bright field and fluorescence images, (2) phytoplankton analysis and recognition, and (3) training facilities for new taxa. It enables characterization of aqueous specimens by their populations. The system is described in detail with emphasis on image analytical aspects. Plankton chambers are scanned by sizable grids, divers objective(s), and up to four fluorescence spectral bands. Acquisition positions are focused and digitized by a TV camera and archived on disk. The image data sets are evaluated by a large set of quantitative features. Automatic classifications for a number of organisms are developed and embedded in the program. Interactive programs for the design of training sets were additionally implemented. A long-term sampling period of 23 weeks from two ponds at two different locations each was performed to generate a reliable data set for training and testing purposes. These data were used to present this system's results for phytoplankton structure characterization. PLASA represents an automatic system, comprising all steps from specimen processing to algae identification up to species level and quantification.

In the age of ever-increasing "-omics" studies, the accurate and statistically robust determination of microbial cell numbers within often-complex samples remains a key task in microbial ecology. Microscopic quantification is still the only method to enumerate specific subgroups of microbial clades within complex communities by, for example, fluorescence in situ hybridization (FISH). In this study, we improved an existing automatic image acquisition and cell enumeration system and adapted it for usage at high seas on board an oceanographic research ship. The system was evaluated by testing settings such as minimal pixel area and image exposure times ashore under stable laboratory conditions before being brought on board and tested under various wind and wave conditions. The system was robust enough to produce high-quality images even with ship heaves of up to 3 m and pitch and roll angles of up to 6.3°. On board the research ship, on average, 25% of the images acquired from plankton samples on filter membranes could be used for cell enumeration. Automated enumeration was highly correlated with manual counts (r(2) > 0.9). Even the smallest of microbial cells in the open ocean, members of the alphaproteobacterial SAR11 clade, could be confidently detected and enumerated. The automated image acquisition and cell enumeration system developed here enables an accurate and reproducible determination of microbial cell counts in planktonic samples and allows insight into the abundance and distribution of specific microorganisms already on board within a few hours.IMPORTANCE In this research article, we report on a new system and software pipeline, which allows for an easy and quick image acquisition and the subsequent enumeration of cells in the acquired images. We put this pipeline through vigorous testing and compared it to manual microscopy counts of microbial cells on membrane filters. Furthermore, we tested this system at sea on board a marine research vessel and counted bacteria on board within a few hours after the retrieval of water samples. The imaging and counting system described here has been successfully applied to a number of laboratory-based studies and allowed the quantification of thousands of samples and FISH preparations (see, e.g., H. Teeling, B. M. Fuchs, D. Becher, C. Klockow, A. Gardebrecht, C. M. Bennke, M. Kassabgy, S. Huang, A. J. Mann, J. Waldmann, M. Weber, A. Klindworth, A. Otto, J. Lange, J. Bernhardt, C. Reinsch, M. Hecker, J. Peplies, F. D. Bockelmann, U. Callies, G. Gerdts, A. Wichels, K. H. Wiltshire, F. O. Glöckner, T. Schweder, and R. Amann, Science 336:608-611, 2012, http://dx.doi.org/10.1126/science.1218344). We adjusted the standard image acquisition software to withstand ship movements. This system will allow for more targeted sampling of the microbial community, leading to a better understanding of the role of microorganisms in the global oceans.

Automatic Multiple Sensor Data Acquisition System in a Real-time Production Environment

Covers advancements in spacecraft and tactical and strategic missile systems, including subsystem design and application, mission design and analysis, materials and structures, developments in space sciences, space processing and manufacturing, space operations, and applications of space technologies to other fields.

Image blurring as a result of patient motion, including organ movement, can cause loss of sensitivity in the detection of disease. The use of gated protocols using external signals to synchronize the acquisition with the motion of the organ of interest may provide a solution. Although such a solution has been implemented in cardiac imaging, the implementation of respiratory gating is more challenging considering the irregular nature of respiratory motion. In this work we investigated the use of two different physiological signals; namely respiratory flow and impedance plethysmography for synchronization of pulmonary scintigraphy with respiratory motion. An acquisition and post-processing signal interface was developed using LabVIEW in order to allow detection and comparison of the two signals for the same patient. Methodology was also developed for the rejection of irregular respiratory cycles based on mean amplitude, overall cycle duration and the cycle inspiration to expiration duration ratio (I/E). Rejection criteria based on tidal volume were also examined using the respiratory flow signal. Our data demonstrate that the two respiratory signals investigated are equivalent with only a phase shift difference present. In the case of respiratory flow, irregular cycles were rejected by setting acceptance limits at 40% and 30% around the mean for the I/E and the amplitude or duration of the cycle respectively. In the case of impedance plethysmography a limit of 50% for all rejection criteria was found to be optimum. Finally, a dynamic acquisition protocol was developed and tested providing synchronized scintigraphic images using both types of recorded respiratory signals.

An automatic biomedical acquisition system for hospital registration is proposed. The system consists of the guide system, the acquisition device and the biomedical measuring devices. The guide system installed in control unit facilitates user to interact with the system properly. An acquisition device (Hub) is used to acquire data from attached measuring devices through RS-232 ports and then transfers measured information to the control unit. Several measuring devices are attached to the Hub including the height meter that we have developed based on an ultrasonic sensor. In the experiment section, the accuracies of both the Hub and the height meter were performed. The results showed the excellent transmission reliability of the Hub and the accurate measurement of the height using our height meter.

In order to obtain the asphalt pavement texture information in real time and accurately monitor the anti-skid performance of the road pavement, an automatic close range photogrammetry system (ACPR system) was proposed and built based on the circle arranged three cameras close range photogrammetry (CPR) technology to obtain the asphalt pavement surface texture. Automatic image acquisition and 3D reconstruction were achieved by the ACPR system. Sand patch method and laser scanning method (ZGScan) were used to collect the on-site comparison test of the asphalt pavement texture. Mean texture depth (MTD) and root mean square roughness (RSMR) were chosen as the statistical indicators of road surface texture. The results show that the texture data obtained by ACPR system has relatively high accuracy and efficiency, and the recognition accuracy is close to 0.02mm. The ACPR system improves the efficiency and accuracy of traditional close range photogrammetry and provides real-time and effective road surface anti-skid information for subsequent safety braking of autonomous vehicle.

Respiratory gating is commonly used to reduce motion artifacts in positron emission tomography (PET). Clinically established methods for respiratory gating in PET require contact to the patient or a direct optical line between the sensor and the patient's torso and time consuming preparation. In this work, a contactless method for capturing a respiratory signal during PET is presented based on continuous-wave radar. The proposed method relies on the principle of emitting an electromagnetic wave and detecting the phase shift of the reflected wave, modulated due to the respiratory movement of the patient's torso. A 24 GHz carrier frequency was chosen allowing wave propagation through plastic and clothing with high reflections at the skin surface. A detector module and signal processing algorithms were developed to extract a quantitative respiratory signal. The sensor was validated using a high precision linear table. During volunteer measurements and [(18)F] FDG PET scans, the radar sensor was positioned inside the scanner bore of a PET/computed tomography scanner. As reference, pressure belt (one volunteer), depth camera-based (two volunteers, two patients), and PET data-driven (six patients) signals were acquired simultaneously and the signal correlation was quantified. The developed system demonstrated a high measurement accuracy for movement detection within the submillimeter range. With the proposed method, small displacements of 25 μm could be detected, not considerably influenced by clothing or blankets. From the patient studies, the extracted respiratory radar signals revealed high correlation (Pearson correlation coefficient) to those derived from the external pressure belt and depth camera signals (r = 0.69-0.99) and moderate correlation to those of the internal data-driven signals (r = 0.53-0.70). In some cases, a cardiac signal could be visualized, due to the representation of the mechanical heart motion on the skin. Accurate respiratory signals were obtained successfully by the proposed method with high spatial and temporal resolution. By working without contact and passing through clothing and blankets, this approach minimizes preparation time and increases the convenience of the patient during the scan.

Initially, the ability of personal computers to perform signal processing or multivariate analysis was severely limited by small memory address space and lack of scientific language support. Recently, however, this situation has changed, with large memory sizes common and with the availability of mainframe languages such as FORTRAN-77 to support complex and double-precision expressions. Today, personal computers can be applied to data collection, multivariate analysis, pattern classification, simulation of signal processing hardware, and other engineering applications. We discuss the conversion of mainframe data analysis software for personal computers, and the use of high-resolution personal computer graphics for data displays. The process is illustrated with the conversion of part of the IEEE signal processing library and of the ARTHUR81 multivariate analysis routines to run on a personal computer. Timing and accuracy results are given for two personal computers--the TI Professional and the IBM PC AT. The use of a personal computer to validate data, obtain measurement statistics, perform classification and cluster analysis, and perform modern spectral analysis is illustrated with run information and typical output displays.

Endoscopic ultrasound-guided portal pressure gradient (EUS-PPG) measurement is a promising alternative to hepatic venous pressure gradient (HVPG) assessment, especially in settings where HVPG is unavailable or limited. The commercial 25-gauge (25G) system showed good correlation with the hepatic venous pressure gradient (HVPG). However, the 25G has drawbacks due to its small caliber and the proprietary pressure transducer. The aim of this study was to validate a custom-built 22G conventional intravascular pressure transducer system (22G EUS-PPG). In this prospective cohort study, 26 patients underwent EUS-PPG measurement using both systems during the same session. The primary outcome was the correlation of PPG values. Secondary outcomes included the correlation and variability of portal vein pressure (PVP) and hepatic vein pressure (HVP) measured by both systems. PPG values showed excellent correlation of both systems (r=0.901, p<0.001). 25G EUS-PPG correctly identified clinically significant portal hypertension (CSPH, defined as PPG ≥10mmHg) in 25 of 26 (96.2%) cases. Portal vein and hepatic vein pressures also correlated significantly (r=0.776 and r=0.673, respectively) between both systems. Variability within both systems was very low to low. EUS-PPG measurements obtained using the commercial 25G and custom-built 22G EUS-PPG systems were validated. The custom-built 22G system excels due to pressure-tracing based quality control, availability and cost-efficiency.

A sensor to measure rapidly changing pressures in an explosive air blast requires high bandwidth and high spatial resolution. For such an application a low-cost, electrically isolated sensor is particularly attractive. We describe an optical fibre-based pressure sensor that meets these requirements. The sensor is subjected to an experimental explosive-blast measurement test and the results are discussed with respect to the sensor performance and compared with a simple blast-wave model and conventional pressure transducers.

In order to do the deformation characteristic tests on marble of which the geostress level is above 60MPa, a set of rigid pressure plates test equipment for center hole method and an automatic servo and acquisition system is developed. It consists of power transmission system, servo load system and measurement system. This paper mainly introduces the system structure, working principle and functions. It is shown by the application in a deep buried tunnel in a hydropower project that the equipment system has high loads, high precision, stable, reliable, and easy to operate. It can solve rock mass deformation test question under high stress and achieve good application effect.

Real-time perception of rock–machine interaction information in TBM tunnelling using muck image analysis

In recent years, there has been increasing interest in the use of automatic computer-based systems for the detection of eye diseases such as glaucoma, age-related macular degeneration and diabetic retinopathy. However, in practice, retinal image quality is a big concern as automatic systems without consideration of degraded image quality will likely generate unreliable results. In this paper, an automatic retinal image quality assessment system (ARIES) is introduced to assess both image quality of the whole image and focal regions of interest. ARIES achieves 99.54% accuracy in distinguishing fundus images from other types of images through a retinal image identification step in a dataset of 35342 images. The system employs high level image quality measures (HIQM) to perform image quality assessment, and achieves areas under curve (AUCs) of 0.958 and 0.987 for whole image and optic disk region respectively in a testing dataset of 370 images. ARIES acts as a form of automatic quality control which ensures good quality images are used for processing, and can also be used to alert operators of poor quality images at the time of acquisition.