Extraction of Airways with Probabilistic State-space Models and Bayesian Smoothing

Segmenting tree structures is common in several image processing applications. In medical image analysis, reliable segmentations of airways, vessels, neurons and other tree structures can enable important clinical applications. We present a framework for tracking tree structures comprising of elongated branches using probabilistic state-space models and Bayesian smoothing. Unlike most existing methods that proceed with sequential tracking of branches, we present an exploratory method, that is less sensitive to local anomalies in the data due to acquisition noise and/or interfering structures. The evolution of individual branches is modelled using a process model and the observed data is incorporated into the update step of the Bayesian smoother using a measurement model that is based on a multi-scale blob detector. Bayesian smoothing is performed using the RTS (Rauch-Tung-Striebel) smoother, which provides Gaussian density estimates of branch states at each tracking step. We select likely branch seed points automatically based on the response of the blob detection and track from all such seed points using the RTS smoother. We use covariance of the marginal posterior density estimated for each branch to discriminate false positive and true positive branches. The method is evaluated on 3D chest CT scans to track airways. We show that the presented method results in additional branches compared to a baseline method based on region growing on probability images.Comment: 10 pages. Pre-print of the paper accepted at Workshop on Graphs in Biomedical Image Analysis. MICCAI 2017. Quebec Cit

Towards defining reference materials for extracellular vesicle size, concentration, refractive index and epitope abundance

Accurate characterization of extracellular vesicles (EVs) is critical to explore their diagnostic and therapeutic applications. As the EV research field has developed, so too have the techniques used to characterize them. The development of reference materials is required for the standardization of these techniques. This work, initiated from the ISEV 2017 Biomarker Workshop in Birmingham, UK, and with further discussion during the ISEV 2019 Standardization Workshop in Ghent, Belgium, sets out to elucidate which reference materials are required and which are currently available to standardize commonly used analysis platforms for characterizing EV size, concentration, refractive index, and epitope expression. Due to their predominant use, a particular focus is placed on the optical methods nanoparticle tracking analysis and flow cytometry.Comment: 30 pages, 6 figures, 2 table

Outcomes of the International Oceanographic Data and Information Exchange Ocean Biogeographic Information System OBIS-Event-Data Workshop on Animal Tagging and Tracking

The Ocean Biogeographic Information System (OBIS) began in 2000 as the repository for data from the Census of Marine Life. Since that time, OBIS has expanded its goals beyond simply hosting data to supporting more aspects of marine conservation (Pooter et al. 2017). In order to accomplish those goals, the OBIS secretariat in partnership with its European node (EurOBIS) hosted at the Flanders Marine Institute (VLIZ, Belgium), and the Intergovernmental Oceanographic Commission (IOC) Committee on International Oceanographic Data and Information Exchange (IODE, 23rd session, March 2015, Brugge) established a 2-year pilot project to address a particularly problematic issue that environmental data collected as part of marine biological research were being disassociated from the biological data. OBIS-Event-Data is the solution that was developed from that pilot project, which devised a method for keeping environmental data together with the biological data (Pooter et al. 2017). OBIS is seeking early adopters of the new data standard OBIS-Event-Data from among the marine biodiversity monitoring communities, to further validate the data standard, and develop data products and scientific applications to support the enhancement of Biological and Ecosystem Essential Ocean Variables (EOVs) in the framework of the Global Ocean Observing System (GOOS) and the Marine Biodiversity Observation Network of the Group on Earth Observations (GEO BON MBON). After the successful 2-year IODE pilot project OBIS-ENV-DATA, the IOC established a new 2-year IODE pilot project OBIS-Event-Data for Scientific Applications (2017-2019). The OBIS-Event-Data data standard, building on Darwin Core, provides a technical solution for combined biological and environmental data, and incorporates details about sampling methods and effort, including event hierarchy. It also implements standardization of parameters involved in biological, environmental, and sampling details using an international standard controlled vocabulary (British Oceanographic Data Centre Natural Environment Research Council). A workshop organized by IODE/OBIS in April brought together major animal tagging and tracking networks such as the Ocean Tracking Network (OTN), the Animal Telemetry Network (ATN), the Integrated Marine Observing System (IMOS), the European Tracking Network (ETN) and the Acoustic Tracking Array Platform (ATAP) to test the OBIS-Event- Data standard through the development of some data products and science applications. Additionally, this workshop contributes to the further maturation of the GOOS EOV on fish as well as the EOV on birds, mammals and turtles. We will present the outcomes as well as any lessons learned from this workshop on problems, solutions, and applications of using Darwin Core/OBIS-Event-Data for biologging data

The Evolution of First Person Vision Methods: A Survey

The emergence of new wearable technologies such as action cameras and smart-glasses has increased the interest of computer vision scientists in the First Person perspective. Nowadays, this field is attracting attention and investments of companies aiming to develop commercial devices with First Person Vision recording capabilities. Due to this interest, an increasing demand of methods to process these videos, possibly in real-time, is expected. Current approaches present a particular combinations of different image features and quantitative methods to accomplish specific objectives like object detection, activity recognition, user machine interaction and so on. This paper summarizes the evolution of the state of the art in First Person Vision video analysis between 1997 and 2014, highlighting, among others, most commonly used features, methods, challenges and opportunities within the field.Comment: First Person Vision, Egocentric Vision, Wearable Devices, Smart Glasses, Computer Vision, Video Analytics, Human-machine Interactio

Bibliographic Review on Distributed Kalman Filtering

In recent years, a compelling need has arisen to understand the effects of distributed information structures on estimation and filtering. In this paper, a bibliographical review on distributed Kalman filtering (DKF) is provided.\ud The paper contains a classification of different approaches and methods involved to DKF. The applications of DKF are also discussed and explained separately. A comparison of different approaches is briefly carried out. Focuses on the contemporary research are also addressed with emphasis on the practical applications of the techniques. An exhaustive list of publications, linked directly or indirectly to DKF in the open literature, is compiled to provide an overall picture of different developing aspects of this area