Browsing by Subject "Mapping"

Now showing 1 - 3 of 3
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    Distributed Monocular SLAM for Indoor Map Building
    (Hindawi, 2017) Egodagamage, Ruwan; Tuceryan, Mihran; Computer and Information Science, School of Science
    Utilization and generation of indoor maps are critical elements in accurate indoor tracking. Simultaneous Localization and Mapping (SLAM) is one of the main techniques for such map generation. In SLAM an agent generates a map of an unknown environment while estimating its location in it. Ubiquitous cameras lead to monocular visual SLAM, where a camera is the only sensing device for the SLAM process. In modern applications, multiple mobile agents may be involved in the generation of such maps, thus requiring a distributed computational framework. Each agent can generate its own local map, which can then be combined into a map covering a larger area. By doing so, they can cover a given environment faster than a single agent. Furthermore, they can interact with each other in the same environment, making this framework more practical, especially for collaborative applications such as augmented reality. One of the main challenges of distributed SLAM is identifying overlapping maps, especially when relative starting positions of agents are unknown. In this paper, we are proposing a system having multiple monocular agents, with unknown relative starting positions, which generates a semidense global map of the environment.
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    From Hometown to Practice: Mapping and Analyzing the Medical Student Pipeline at the Indiana University School of Medicine
    (2019-10) Fancher, Laurie Michelle; Wilson, Jeffrey; Kochhar, Komal; Lulla, Vijay
    Indiana University School of Medicine (IUSM) teaches approximately 350 medical students each year. These students come from varied backgrounds and eventually end up practicing in a vast array of clinical specialties and settings. It is extremely important to monitor specialties and practice locations to understand exactly how IUSM is fulfilling physician workforce needs. This knowledge can help policymakers and school administrators shape programs and policies to better fulfill physician workforce needs. Geographic information technologies provide a framework to organize, analyze and visualize medical student data. Maps are a convenient and easily understandable method of conveying information with a location-based component. This project represents a step towards creating a coherent student database visualized with maps. Using data about the graduating classes from 2011-2018, a database was created that linked together geographic information of students from the various segments of their medical education such as residency, fellowship, and practice location. ArcGIS 10.5 was used to produce maps visualizing segments of this database. These maps also served to answer questions about the medical student graduates at IUSM, such as how many came from an in-state location and how many practice in-state. SPSS 25 was also used to compare results of various segments of the medical education pipeline. The database proves to be an incredibly necessary tool for keeping track of all IUSM graduates. Coherent, clean, and complete data is necessary for researchers at all levels as well as administrators. Keeping data up to date and centralized is essential and this project provides an easily updateable and useable format. The maps created from this database are also useful in showing trends across the graduates of IUSM, such as the Indiana counties that the graduates are most likely to practice in or the likelihood of practicing in specific shortage areas.
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    The LOINC RSNA radiology playbook - a unified terminology for radiology procedures
    (Oxford Academic, 2018-07-01) Vreeman, Daniel J.; Abhyankar, Swapna; Wang, Kenneth C.; Carr, Christopher; Collins, Beverly; Rubin, Daniel L.; Langlotz, Curtis P.; Medicine, School of Medicine
    Objective: This paper describes the unified LOINC/RSNA Radiology Playbook and the process by which it was produced. Methods: The Regenstrief Institute and the Radiological Society of North America (RSNA) developed a unification plan consisting of six objectives 1) develop a unified model for radiology procedure names that represents the attributes with an extensible set of values, 2) transform existing LOINC procedure codes into the unified model representation, 3) create a mapping between all the attribute values used in the unified model as coded in LOINC (ie, LOINC Parts) and their equivalent concepts in RadLex, 4) create a mapping between the existing procedure codes in the RadLex Core Playbook and the corresponding codes in LOINC, 5) develop a single integrated governance process for managing the unified terminology, and 6) publicly distribute the terminology artifacts. Results: We developed a unified model and instantiated it in a new LOINC release artifact that contains the LOINC codes and display name (ie LONG_COMMON_NAME) for each procedure, mappings between LOINC and the RSNA Playbook at the procedure code level, and connections between procedure terms and their attribute values that are expressed as LOINC Parts and RadLex IDs. We transformed all the existing LOINC content into the new model and publicly distributed it in standard releases. The organizations have also developed a joint governance process for ongoing maintenance of the terminology. Conclusions: The LOINC/RSNA Radiology Playbook provides a universal terminology standard for radiology orders and results.