Rationale And Objectives: The Liver Imaging Reporting and Data System (LI-RADS) can enhance communication between radiologists and clinicians if applied consistently. We identified an institutional need to improve liver imaging report standardization and developed handheld and desktop software to serve this purpose.
Materials And Methods: We developed two complementary applications that implement the LI-RADS schema. A mobile application for iOS devices written in the Objective-C language allows for rapid characterization of hepatic observations under a variety of circumstances. A desktop application written in the Java language allows for comprehensive observation characterization and standardized report text generation. We chose the applications' languages and feature sets based on the computing resources of target platforms, anticipated usage scenarios, and ease of application installation, deployment, and updating.
Results: Our primary results are the publication of the core source code implementing the LI-RADS algorithm and the availability of the applications for use worldwide via our website, http://www.liradsapp.com/. The Java application is free open-source software that can be integrated into nearly any vendor's reporting system. The iOS application is distributed through Apple's iTunes App Store. Observation categorizations of both programs have been manually validated to be correct. The iOS application has been used to characterize liver tumors during multidisciplinary conferences of our institution, and several faculty members, fellows, and residents have adopted the generated text of Java application into their diagnostic reports.
Conclusions: Although these two applications were developed for the specific reporting requirements of our liver tumor service, we intend to apply this development model to other diseases as well. Through semiautomated structured report generation and observation characterization, we aim to improve patient care while increasing radiologist efficiency.
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http://dx.doi.org/10.1016/j.acra.2013.12.014 | DOI Listing |
Childs Nerv Syst
December 2024
Department of Neurosurgery, Osaka Women's and Children's Hospital, Izumi, Osaka, 594-1101, Japan.
Purpose: This study presents a MATrix LABoratory (MATLAB)-based methodology for calculating intracranial volumes from head computed tomography (CT) data and compares it with established methods.
Methods: Regions of interest (ROI) were manually segmented on CT images using a stylus pen, facilitated by mirroring a computer desktop onto a tablet. The volumetric process involved three main steps: (1) calculating the volume of a single voxel, (2) counting the total number of voxels within the segmented ROI, and (3) multiplying this voxel count by the single-voxel volume.
Background: Investment in mobile devices to support primary or elementary education is increasing and must be informed by robust evidence to demonstrate impact. This systematic review of randomised controlled trials sought to identify the overall impact of mobile devices to support literacy and numeracy outcomes in mainstream primary classrooms.
Objectives: The aim of this systematic review was to understand how mobile devices are used in primary/elementary education around the world, and in particular, determine how activities undertaken using mobile devices in the primary classroom might impact literacy and numeracy attainment for the pupils involved.
Background: Measurement of the efficacy of the networks of attention is a frequent component of research in cognitive and clinical neuroscience. Developed in 2002, the Attention Network Test (ANT), has become the most widely used tool for this purpose.
New Method: In 2017 a more engaging, game-like tool based on the ANT, called the AttentionTrip was described.
J Dent Sci
April 2024
Department of Conservative Dentistry, Dental Research Institute, Seoul National University School of Dentistry, Seoul, Republic of Korea.
J Prosthet Dent
April 2024
Associate Professor, Adelaide Dental School, University of Adelaide, Adelaide, Australia.
Statement Of Problem: Whether the use of an external graphics processing unit (eGPU) and a handheld computer prolongs the operation time for 3-dimensional (3D) intraoral scanning or produces clinically unacceptable scans is unclear.
Purpose: The purpose of this in vitro study was to compare the 3D intraoral scan accuracy and scan time of a small portable device and an eGPU with desktop-grade workstations.
Material And Methods: A handheld computer, a laptop, a desktop workstation, and an external graphics card were used to scan a 3D printed set of maxillary and mandibular casts 10 consecutive times using an intraoral scanner.
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