Advanced Medical Imaging Tools (AMIT)
Advanced Medical Imaging Tools (AMIT) is a collection of projects in CEB which are focused on developing algorithmic techniques to enhance the use of biomedical image, signal, and text data for research and potential clinical applications. The AMIT projects include work in developing cancer imaging tools, lung x-ray classification, cell classification for malaria identification, and computational techniques for neuroimaging.
Boundary Marking Tool
The Boundary Marking Tool 2 (BMT2) was developed by the National Library of Medicine in collaboration with the National Cancer Institute. The BMT2 is software that allows the manual marking of boundaries on digitized images and the recording of diagnostic or interpretive data that applies to these individual boundaries, or to the image as a whole.
CEB Histology Image Assistant (CHIA)
The CEB Histology Image Assistant (CHIA) provides Web access to digitized histology images for expert review and evaluation. Since these images tend to be extremely large, CHIA uses technology to access and display only the part of the image that corresponds to the user’s current zoom and pan level.
Multimedia Database Tool (MDT)
The Multimedia Database Tool (MDT) provides text-searchable access to databases containing both text and images. With the MDT, users may use a graphical user interface to pose a query based on values of text fields (including numeric values), and retrieve database records, including associated images, that satisfy the query. The MDT display is divided into scrollable areas for the returned text, and for the returned images. The returned data may be downloaded to the user’s local computer.
Since May 2010, the Teaching Tool (TT) has provided continuous support for medical residents and colposcopy practitioners to take two online exams to evaluate proficiency of screening and management techniques for abnormalities of the uterine cervix, and related conditions.
Clinical Vocabulary Standards
Multiple projects in this area continue to promote the development, enhancement, and adoption of clinical vocabulary standards. Inter-terminology mapping promotes the use of standard terminologies by creating maps to administrative terminologies, which allows re-use of encoded clinical data.
Computer-Aided TB Screening for HIV+ Population Using Chest X-Rays
This project intends to leverage in-house expertise in image processing to screen HIV-positive patients in rural Kenya for evidence of pulmonary tuberculosis (TB) in chest x-rays. We have provided AMPATH with lightweight digital x-ray units readily transportable in rural areas to take chest x-rays (CXR) of the population and screen them for the presence of disease.
Lost Person Finder
The LPF project investigates solutions for speeding family reunification during and after mass casualty events so that family, friends and neighbors can rapidly locate and reunite with one another during and after a disaster.
People Locator® is the website (https://pl.nlm.nih.gov) where family and friends can search for and report missing persons after mass casualty events. The ReUnite app serves the same purpose on Android or iOS devices.
ReUnite® is a tool for Android and iOS users to quickly search and report post-disaster to assist in family reunification. After a disaster, the U.S. National Library of Medicine’s PEOPLE LOCATOR® website (https://pl.nlm.nih.gov) opens an event. The app can then be used for reporting and searching missing or found persons in the event.
TriagePic® is the name of the software that is both an app and application for searching and reporting data to the TriageTrak database.
To improve malaria diagnostics, the Lister Hill National Center for Biomedical Communications, an R&D division of the US National Library of Medicine, in collaboration with NIH’s National Institute of Allergy and Infectious Diseases (NIAID) and Mahidol-Oxford University, is developing a fully-automated system for parasite detection and counting in blood films.
Medical Article Records System (MARS)
The Medical Article Records System (MARS)project develops automated systems to extract bibliographic text from journal articles, in both paper as well as electronic forms. For the approximately 1000 journal titles that arrive at NLM in paper form, a production MARS system combines document scanning, optical character recognition (OCR), and rule-based and machine learning algorithms to yield citation data that NLM’s indexers use to complete bibliographic records for MEDLINE.
Publisher Data Review System (PDRS)
The PDRS system provides operator data missing from the XML citations sent in directly by publishers (such as databank accession numbers, grant numbers, grant supports, investigator names, and PubMed IDs of commented articles) and as a result it speeds up the creation process and reduces manual data entry costs in completing citation records for MEDLINE.
The ORBIT Project is designed to facilitate efficient registration of, searching for, and tracking of biomedical informatics resources including software, knowledge bases, database schema, data sets, special interest groups, and funding agencies.
Open Access Biomedical Image Search Engine
Repository for Informed Decision Making (RIDeM)
The long-term goal of the Repository for Informed Decision Making is to provide access to key facts needed to support clinical decision making. The facts are extracted from biomedical literature and clinical text sources. The development of the Repository is guided by the Evidence Based Medicine (EBM) principles for finding and appraising information.
System For Preservation of Electronic Resources (SPER)
SPER is a part of the Digital Preservation Research project at Lister Hill Center’s Communications Engineering Branch. Its main objective is to help in the long term preservation of digitized or born-digital documents at the National Library of Medicine in a cost-effective way.
Turning the Pages
Using touchscreen technology and animation software, the digitized images of rare and beautiful historic books in the biomedical sciences are offered at kiosks at the U.S. National Library of Medicine