TY - JOUR A1 - Pfitzner, Christian A1 - May, Stefan A1 - Nüchter, Andreas T1 - Body weight estimation for dose-finding and health monitoring of lying, standing and walking patients based on RGB-D data JF - Sensors N2 - This paper describes the estimation of the body weight of a person in front of an RGB-D camera. A survey of different methods for body weight estimation based on depth sensors is given. First, an estimation of people standing in front of a camera is presented. Second, an approach based on a stream of depth images is used to obtain the body weight of a person walking towards a sensor. The algorithm first extracts features from a point cloud and forwards them to an artificial neural network (ANN) to obtain an estimation of body weight. Besides the algorithm for the estimation, this paper further presents an open-access dataset based on measurements from a trauma room in a hospital as well as data from visitors of a public event. In total, the dataset contains 439 measurements. The article illustrates the efficiency of the approach with experiments with persons lying down in a hospital, standing persons, and walking persons. Applicable scenarios for the presented algorithm are body weight-related dosing of emergency patients. KW - RGB-D KW - human body weight KW - image processing KW - kinect KW - machine learning KW - perception KW - segmentation KW - sensor fusion KW - stroke KW - thermal camera Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-176642 VL - 18 IS - 5 ER - TY - JOUR A1 - Herz, Stefan A1 - Stefanescu, Maria R. A1 - Lohr, David A1 - Vogel, Patrick A1 - Kosmala, Aleksander A1 - Terekhov, Maxim A1 - Weng, Andreas M. A1 - Grunz, Jan-Peter A1 - Bley, Thorsten A. A1 - Schreiber, Laura M. T1 - Effects of image homogeneity on stenosis visualization at 7 T in a coronary artery phantom study: With and without B1-shimming and parallel transmission JF - PloS One N2 - Background To investigate the effects of B\(_1\)-shimming and radiofrequency (RF) parallel transmission (pTX) on the visualization and quantification of the degree of stenosis in a coronary artery phantom using 7 Tesla (7 T) magnetic resonance imaging (MRI). Methods Stenosis phantoms with different grades of stenosis (0%, 20%, 40%, 60%, 80%, and 100%; 5 mm inner vessel diameter) were produced using 3D printing (clear resin). Phantoms were imaged with four different concentrations of diluted Gd-DOTA representing established arterial concentrations after intravenous injection in humans. Samples were centrally positioned in a thorax phantom of 30 cm diameter filled with a custom-made liquid featuring dielectric properties of muscle tissue. MRI was performed on a 7 T whole-body system. 2D-gradient-echo sequences were acquired with an 8-channel transmit 16-channel receive (8 Tx / 16 Rx) cardiac array prototype coil with and without pTX mode. Measurements were compared to those obtained with identical scan parameters using a commercially available 1 Tx / 16 Rx single transmit coil (sTX). To assess reproducibility, measurements (n = 15) were repeated at different horizontal angles with respect to the B0-field. Results B\(_1\)-shimming and pTX markedly improved flip angle homogeneity across the thorax phantom yielding a distinctly increased signal-to-noise ratio (SNR) averaged over a whole slice relative to non-manipulated RF fields. Images without B\(_1\)-shimming showed shading artifacts due to local B\(_1\)\(^+\)-field inhomogeneities, which hampered stenosis quantification in severe cases. In contrast, B\(_1\)-shimming and pTX provided superior image homogeneity. Compared with a conventional sTX coil higher grade stenoses (60% and 80%) were graded significantly (p<0.01) more precise. Mild to moderate grade stenoses did not show significant differences. Overall, SNR was distinctly higher with B\(_1\)-shimming and pTX than with the conventional sTX coil (inside the stenosis phantoms 14%, outside the phantoms 32%). Both full and half concentration (10.2 mM and 5.1 mM) of a conventional Gd-DOTA dose for humans were equally suitable for stenosis evaluation in this phantom study. Conclusions B\(_1\)-shimming and pTX at 7 T can distinctly improve image homogeneity and therefore provide considerably more accurate MR image analysis, which is beneficial for imaging of small vessel structures. KW - stenosis KW - magnetic resonance imaging KW - thorax KW - in vivo imaging KW - coronary arteries KW - image processing KW - 3D printing KW - signal to noise ratio Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-300129 VL - 17 IS - 6 ER - TY - JOUR A1 - Al-Zaben, Naim A1 - Medyukhina, Anna A1 - Dietrich, Stefanie A1 - Marolda, Alessandra A1 - Hünniger, Kerstin A1 - Kurzai, Oliver A1 - Figge, Marc Thilo T1 - Automated tracking of label-free cells with enhanced recognition of whole tracks JF - Scientific Reports N2 - Migration and interactions of immune cells are routinely studied by time-lapse microscopy of in vitro migration and confrontation assays. To objectively quantify the dynamic behavior of cells, software tools for automated cell tracking can be applied. However, many existing tracking algorithms recognize only rather short fragments of a whole cell track and rely on cell staining to enhance cell segmentation. While our previously developed segmentation approach enables tracking of label-free cells, it still suffers from frequently recognizing only short track fragments. In this study, we identify sources of track fragmentation and provide solutions to obtain longer cell tracks. This is achieved by improving the detection of low-contrast cells and by optimizing the value of the gap size parameter, which defines the number of missing cell positions between track fragments that is accepted for still connecting them into one track. We find that the enhanced track recognition increases the average length of cell tracks up to 2.2-fold. Recognizing cell tracks as a whole will enable studying and quantifying more complex patterns of cell behavior, e.g. switches in migration mode or dependence of the phagocytosis efficiency on the number and type of preceding interactions. Such quantitative analyses will improve our understanding of how immune cells interact and function in health and disease. KW - image processing KW - software Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-221093 VL - 9 ER - TY - JOUR A1 - Ahmed, Zeeshan A1 - Zeeshan, Saman A1 - Dandekar, Thomas T1 - Mining biomedical images towards valuable information retrieval in biomedical and life sciences JF - Database - The Journal of Biological Databases and Curation N2 - Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries. KW - humans KW - software KW - image processing KW - animals KW - computer-assisted KW - data mining/methods KW - natural language processing Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-162697 VL - 2016 ER -