ARmedViewer, an augmented-reality-based fast 3D reslicer for medical image data on mobile devices: A feasibility study. (March 2021)

• Record Type: Journal Article
• Authors: Sveinsson, Bragi; Koonjoo, Neha; Rosen, Matthew S
• Is Part Of: Computer methods and programs in biomedicine. Volume 200(2021)
• Publication Date: 2021-03
• Subjects: Augmented reality -- Medical imaging -- Mobile device; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2020.105836
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: Great progress has been made in the development of portable medical imaging devices. Medical images are still typically viewed on a computer workstation after acquisition. ARmedViewer was created to view medical images on a mobile device using augmented reality. The program uses a novel way of reslicing 3D image datasets by physically moving the device. Experiments showed ARmedViewer easier, more intuitive, and faster to use than standard software. Abstract: Background and objective : Medical images obtained by methods such as magnetic resonance imaging (MRI) or computed tomography (CT) are typically displayed as a stack of 2D slices, comprising a 3D volume. Often, the anatomy of interest does not fall neatly into the slice plane but rather extends obliquely through several slices. Reformatting the data to show the anatomy in one slice in conventional medical imaging software can require expertise and time. In this work, we present ARmedViewer, a medical image viewing app designed for mobile devices that uses augmented reality technology to display medical image data. An arbitrary plane for displaying the data can be chosen quickly and intuitively by moving the mobile device. Methods : The app ARmedViewer, compiled for an iOS device, was designed to allow a user to easily select from a list of 3D image datasets consisting of header information and image data. The user decides where to place the data, which can be overlaid on actual human anatomy. After loading the dataset, the user can move and rotate the data as desired. 15 users compared the user experience of the app to a common image viewer by answering two user surveys each, one custom and one standardized. The utility of the app was also tested by having two users find a plane through a 3D dataset that displayed 3 randomly placed lesions. This operation was timed and compared between the app and a standard medical image viewer. Results: ARmedViewer was successfully developed and run on an iPhone XS. User interfaces for selecting, placing, moving, reslicing, and displaying the data were operated with ease, even by naïve users. The custom user survey indicated that freely selecting a slice through the data was significantly more intuitive and easier using the app than using a conventional image viewer on a computer workstation, and changing the viewing angle was also significantly more intuitive. The standardized survey indicated a significantly better user experience for the app in several categories, and never significantly worse. The timed reslicing experiments demonstrated the app being faster than the standard image viewer by an average factor of 9. Conclusions : The newly developed ARmedViewer is a portable software tool for easily displaying 3D medical image data overlaid on human anatomy, allowing for easy choice of the viewing plane by intuitively moving the mobile device.