Advanced background modeling with RGB-D sensors through classifiers combination and inter-frame foreground prediction

An innovative background modeling technique that is able to accurately segment foreground regions in RGB-D imagery (RGB plus depth) has been presented in this paper. The technique is based on a Bayesian framework that efficiently fuses different sources of information to segment the foreground. In particular, the final segmentation is obtained by considering a prediction of the foreground regions, carried out by a novel Bayesian Network with a depth-based dynamic model, and, by considering two independent depth and color-based mixture of Gaussians background models. The efficient Bayesian combination of all these data reduces the noise and uncertainties introduced by the color and depth features and the corresponding models. As a result, more compact segmentations, and refined foreground object silhouettes are obtained. Experimental results with different databases suggest that the proposed technique outperforms existing state-of-the-art algorithms

Intelligent Sensors for Human Motion Analysis

The book, "Intelligent Sensors for Human Motion Analysis," contains 17 articles published in the Special Issue of the Sensors journal. These articles deal with many aspects related to the analysis of human movement. New techniques and methods for pose estimation, gait recognition, and fall detection have been proposed and verified. Some of them will trigger further research, and some may become the backbone of commercial systems

Functional pulmonary MRI with ultra-fast steady-state free precession

To date, computed tomography and nuclear medicine techniques are still the reference standard for lung imaging, but radiation exposure is a major concern; especially in case of longitudinal examinations and in children. Therefore, radiation-free imaging is an urgent necessity. Pulmonary magnetic resonance imaging (MRI) is radiation-free, but poses challenges since the low proton density and the presence of strong mesoscopic susceptibility variations considerably reduce the detectable MR signal. As a result, the lung typically appears as a “black hole” with conventional MRI techniques. Recently, ultra-fast balanced steady-state free precession (ufSSFP) methods were proposed for ameliorated lung morphological imaging. In this thesis, ufSSFP is employed to develop and improve several pulmonary functional imaging methods, which can be used in clinical settings using standard MR scanners and equipment. At every breath, the lung expands and contracts, and at every heartbeat, the blood is pumped through the arteries to reach the lung parenchyma. This creates signal modulations associated with pulmonary blood perfusion and ventilation that are detectable by MRI. The second chapter of this thesis focuses on the optimization of time-resolved two-dimensional (2D) ufSSFP for perfusion-weighted and ventilation-weighted imaging of the lung. Subsequently, in the third chapter, three-dimensional (3D) multi-volumetric ufSSFP breath-hold imaging is used to develop a lung model and retrieve the measure α, a novel ventilation-weighted quantitative parameter. Oxygen-enhanced MRI exploits the paramagnetic properties of oxygen dissolved in the blood, acting as a weak T1-shortening contrast agent. When breathing pure oxygen, it reaches only ventilated alveoli of the parenchyma and dissolves only in functional and perfused regions. How ufSSFP imaging in combination with a lung model can be used to calculate robust 3D oxygen enhancement maps is described in the fourth chapter. In addition, in the fifth chapter, 2D inversion recovery ufSSFP imaging is employed to map the T1 and T2 relaxation times of the lung, the change of the relaxation times after hyperoxic conditions, as well as the physiological oxygen wash-in and wash-out time (related to the time needed to shorten T1 after oxygen breathing). The objective of the last chapter of this thesis is the application of 3D ufSSFP imaging before and after intravenous gadolinium-based contrast agent administration for the investigation of signal enhancement ratio (SER) mapping: a rapid technique to visualize perfusion-related diseases of the lung parenchyma. The techniques presented in this thesis using optimized ufSSFP pulse sequences demonstrated potential to reveal new insights on pulmonary function as well as quantification, and might become part of the future standard for the evaluation and follow-up of several lung pathologies

Model-driven registration for multi-parametric renal MRI

The use of MR imaging biomarkers is a promising technique that may assist towards faster prognosis and more accurate diagnosis of diseases like diabetic kidney disease (DKD). The quantification of MR Imaging renal biomarkers from multiparametric MRI is a process that requires a physiological model to be fitted on the data. This process can provide accurate estimates only under the assumption that there is pixelto-pixel correspondence between images acquired over different time points. However, this is rarely the case due to motion artifacts (breathing, involuntary muscle relaxation) introduced during the acquisition. Hence, it is of vital importance for a biomarkers quantification pipeline to include a motion correctionstep in order to properly align the images and enable a more accurate parameter estimation. This study aims in testing whether a Model Driven Registration (MDR), which integrates physiological models in the registration process itself, can serve as a universal solution for the registration of multiparametric renal MRI. MDR is compared with a state-of-the-art model-free motion correction approach for multiparametric MRI, that minimizes a Principal Components Analysis based metric, performing a groupwise registration. The results of the two methods are compared on T1, DTI and DCE-MRI data for a small cohort of 10 DKD patients, obtained from BEAt-DKD project’s digital database. The majority of the evaluation metrics used to compare the two methods indicated that MDR achieved better registration results, while requiring significantly lower computational times. In conclusion, MDR could be considered as the method of choice for motion correction of multiparametric quantitative renal MRI

Methods for the integration of combined PET/MR into radiotherapy planning

Despite recent advances in radiotherapy (RT) there are still tumor types for which a high fraction of recurrences is observed following treatment. Limiting factors in current treatment concepts seem to be inaccuracies in image-based tumor delineation and missing consideration of the biological heterogeneity of individual tumors. In this respect, the abundant anatomical and functional information provided by magnetic resonance imaging (MRI) and positron emission tomography (PET) may lead to major advances in RT treatment. Recently available combined PET/MR scanners allow for the acquisition of simultaneous, intrinsically registered PET/MR data, facilitating their combined analysis for the integration into RT. In this thesis, dedicated methods and algorithms for the analysis and integration of the multimodal PET/MR datasets into RT are developed. In the first part, a method for multimodal deformable registration is developed, to enable the spatial transformation of PET/MR data to the computed tomography used for treatment planning. The second part is concerned with the development of an automatic tumor segmentation algorithm, considering PET and MR information simultaneously. In the last part, a correlation analysis of various functional datasets is motivated and performed in order to support the definition of a biologically adapted dose prescription.Trotz jüngster Fortschritte in der Strahlentherapie (ST) gibt es noch immer Tumorarten mit einem hohen Prozentsatz an Rezidiven nach der Behandlung. Limitierende Faktoren in aktuellen Behandlungskonzepten scheinen vor allem Ungenauigkeiten in der bildbasierten Tumorabgrenzung sowie die fehlende Berücksichtigung der biologischen Heterogenität der einzelnen Tumoren zu sein. In dieser Hinsicht erscheint die Einbeziehung der vielfältigen anatomischen und funktionellen Bildgebungsmöglichkeiten der Magnetresonanztomographie (MRT), sowie der Positronenemissionstomographie (PET), in die ST vielversprechend. Seit kurzem verfügbare PET/MR-Scanner erlauben die Akquisition simultaner, intrinsisch registrierter PET/MR-Datensätze, wodurch deren kombinierte Analyse und Integration in die Therapieplanung erleichtert wird. Diese Arbeit befasst sich mit der Entwicklung von dedizierten Methoden und Algorithmen für die Analyse und Integration der multimodalen PET/MR-Datensätze in die ST. Im ersten Teilprojekt wurde eine Methode zur multimodalen deformierbaren Registrierung entwickelt, um die räumliche Transformation der PET/MR-Daten auf die zur Therapieplanung notwendige Computertomographie-Aufnahme zu ermöglichen. Im zweiten Teil wurde ein Algorithmus zur automatischen Tumorsegmentierung unter simultaner Berücksichtigung von PET- und MR-Information entwickelt. Abschließend wurde im dritten Teil eine Korrelationsanalyse der funktionellen PET- und MR-Datensätze motiviert und ausgeführt, um die Definition einer biologisch adaptierten Dosisverschreibung zu unterstützen

Multiscale Modeling of the Ventricles: From Cellular Electrophysiology to Body Surface Electrocardiograms

This work is focused on different aspects within the loop of multiscale modeling: On the cellular level, effects of adrenergic regulation and the Long-QT syndrome have been investigated. On the organ level, a model for the excitation conduction system was developed and the role of electrophysiological heterogeneities was analyzed. On the torso level a dynamic model of a deforming heart was created and the effects of tissue conductivities on the solution of the forward problem were evaluated

Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion

Argonne National Laboratory annual report of laboratory directed research and development program activities for FY 1995.

The purposes of Argonne's Laboratory Directed Research and Development (LDRD) Program are to encourage the development of novel concepts, enhance the Laboratory's R&D capabilities, and further the development of its strategic initiatives

UAV or Drones for Remote Sensing Applications in GPS/GNSS Enabled and GPS/GNSS Denied Environments

The design of novel UAV systems and the use of UAV platforms integrated with robotic sensing and imaging techniques, as well as the development of processing workflows and the capacity of ultra-high temporal and spatial resolution data, have enabled a rapid uptake of UAVs and drones across several industries and application domains.This book provides a forum for high-quality peer-reviewed papers that broaden awareness and understanding of single- and multiple-UAV developments for remote sensing applications, and associated developments in sensor technology, data processing and communications, and UAV system design and sensing capabilities in GPS-enabled and, more broadly, Global Navigation Satellite System (GNSS)-enabled and GPS/GNSS-denied environments.Contributions include:UAV-based photogrammetry, laser scanning, multispectral imaging, hyperspectral imaging, and thermal imaging;UAV sensor applications; spatial ecology; pest detection; reef; forestry; volcanology; precision agriculture wildlife species tracking; search and rescue; target tracking; atmosphere monitoring; chemical, biological, and natural disaster phenomena; fire prevention, flood prevention; volcanic monitoring; pollution monitoring; microclimates; and land use;Wildlife and target detection and recognition from UAV imagery using deep learning and machine learning techniques;UAV-based change detection

Treatment plan robustness in pancreatic patients treated with scanned ion-beam therapy: Inter- and intra-fractional aspects

Pancreatic cancer is still an unsolved oncological challenge, however radiotherapy with charged particles has been considered a promising approach to improve the patients overall survival. These patients might benefit from dose escalation, although uncertainties during the beam delivery (intra-fractional) or along the treatment course (inter-fractional) can compromise the accuracy of the treatment. In this thesis, inter- and intra-fractional anatomy changes are explored in order to define the potential source of uncertainties, quantify their effect, and to define strategies towards their reduction. Anatomical changes along the course of the treatment showed to lead target under-dosages up to 20% and an increase in the dose to the normal tissues. However, this can be lowered through the selection of beam arrangements from the patient's posterior side and beam-specific margins. From the results of this work, it was concluded that a combination of an Internal Target Volume (ITV), obtained by a geometric expansion of 3 mm from the Clinical Target Volume (CTV), and two oblique posterior beams can reduce the mean V95CTV variations to less than 1%. For other beam directions, the calculation of ITVs including the water-equivalent path length (WEPL), suggested the need for a CTV asymmetric expansion in depth, and minimal in lateral beam direction. Additionally, weekly monitoring of the patient anatomy using computed tomography (CT) might easily be included in the clinical workflow and will assist in the decision of treatment re-planning, when substantial anatomical changes occur. The suggested prediction model was based on the variations of the accumulated WEPL (∆accWEPL) relative to the planning CT, and showed a strong correlation between the ∆accWEPL and the gamma index of the dose distributions. The gamma criterion was selected as dose distribution quality metric, since it includes dosimetric changes in the target and normal tissues. Regarding intra-fractional variations, the induced breathing motion together with a dynamic beam delivery, affect the dose distribution in terms of homogeneity and target coverage. This effect is stronger (∆V95CTV > 10%) for patients with a tumor motion amplitude superior to 5 mm and a highly modulated dose distribution intra- and inter-fields. The concept of modulation index was employed, it showed that different optimisers produce plans with contrasting distribution of the number of particles, resulting in unlike robustness against range and positioning uncertainties. It was concluded that under internal motion, the use of homogeneous plans, multiple beams, and geometric ITVs, originated dose distributions exhibiting a slight mean decrease of the dose homogeneity (H_CTV) and V95CTV of 4% and 1%, respectively. Finally, a first approach to the use of 4D-Magnetic Resonance Imaging (MRI) for motion detection was performed. The results revealed cases of non-linear correlation between the breathing signal (diaphragm position) and the pancreas motion, and variability of the motion amplitude along the acquisition time and between sessions. This reinforces the need of an alternative method, comparative to the use of external surrogates, for simulation of a 4D dose distribution. Therefore, MRI will allow to include baseline drifts, amplitude variations and anatomical alterations in the 4D dose distribution assessment. In summary, the key for a precise delivery of the treatment is the monitoring of anatomical changes, and a prompt reaction in order to minimise or eliminate potential uncertainties. In future, it is expected that the methods suggested in this thesis, the experience gained at HIT on treating moving organs and, the developments in treatment planning and treatment delivery will allow us to move towards the robust plan optimisation, prediction of changes in the dose distribution, and enable treatment without a constant and complex monitoring of the patient's movement