Abstract
The radiology community has adopted several widely used standards for medical image files, including the popular DICOM (Digital Imaging and Communication in Medicine) and NIfTI (Neuroimaging Informatics Technology Initiative) standards. These file formats include image intensities as well as potentially extensive metadata. The NIfTI standard specifies a particular set of header fields describing the image and minimal information about the scan. DICOM headers can include any of >4,000 available metadata attributes spanning a variety of topics. NIfTI files contain all slices for an image series, while DICOM files capture single slices and image series are typically organized into a directory. Each DICOM file contains metadata for the image series as well as the individual image slice. The programming environment R is popular for data analysis due to its free and open code, active ecosystem of tools and users, and excellent system of contributed packages. Currently, many published radiological image analyses are performed with proprietary software or custom unpublished scripts. However, R is increasing in popularity in this area due to several packages for processing and analysis of image files. While these R packages handle image import and processing, no existing package makes image metadata conveniently accessible. Extracting image metadata, combining across slices, and converting to useful formats can be prohibitively cumbersome, especially for DICOM files. We present radtools, an R package for smooth navigation of medical image data. Radtools makes the problem of extracting image metadata trivially simple, providing simple functions to explore and return information in familiar R data structures. Radtools also facilitates extraction of image data and viewing of image slices. The package is freely available under the MIT license at https://github.com/pamelarussell/radtools and is easily installable from the Comprehensive R Archive Network ( https://cran.r-project.org/package=radtools).
Highlights
An R package for smooth navigation of medical image data
The package is freely available under the MIT license at https://github.com/pamelarussell/radtools and is installable from the Comprehensive R Archive Network
Medical image analysis often lies at the boundary of research and the clinic, presenting challenges in both domains
Summary
Volker Schmid , Ludwig Maximilian University of Munich, Munich, Germany. Any reports and responses or comments on the article can be found at the end of the article. An R package for smooth navigation of medical image data. Radtools makes the problem of extracting image metadata trivially simple, providing simple functions to explore and return information in familiar R data structures. Radtools facilitates extraction of image data and viewing of image slices. The package is freely available under the MIT license at https://github.com/pamelarussell/radtools and is installable from the Comprehensive R Archive Network (https://cran.rproject.org/package=radtools). Keywords Medical imaging, DICOM, NIfTI, R package. This article is included in the International Society for Computational Biology Community Journal gateway. This article is included in the RPackage gateway. This article is included in the Neuroconductor collection
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