The Annotation and Image Mark-up Project

Channin, David S.; Mongkolwat, Pattanasak; Kleper, Vladimir; Rubin, Daniel L.

doi:10.1148/radiol.2533090135

Cited by 55 publications

(34 citation statements)

References 4 publications

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“…But in the case of a quantitative imaging procedure that is moving from research-only applications into clinical use, it could be interesting to find a way that does not leave post-processing results "separated" from the context of a hospital information system. It is in this context that the Annotation and Image Markup project was started by the US National Cancer Institute for the creation of a software tool to associate quantitative and descriptive information to images, with the intent to facilitate the use of imaging as biomarker in cancer studies [22].…”

Section: Discussionmentioning

confidence: 99%

Medical Image File Formats

2013

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Image file format is often a confusing aspect for someone wishing to process medical images. This article presents a demystifying overview of the major file formats currently used in medical imaging: Analyze, Neuroimaging Informatics Technology Initiative (Nifti), Minc, and Digital Imaging and Communications in Medicine (Dicom). Concepts common to all file formats, such as pixel depth, photometric interpretation, metadata, and pixel data, are first presented. Then, the characteristics and strengths of the various formats are discussed. The review concludes with some predictive considerations about the future trends in medical image file formats.

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Section: Discussionmentioning

confidence: 99%

Medical Image File Formats

2013

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“…For example, quantitative imaging applications for tracking lesion size over time could parse measurements made on serial imaging examinations. To enable these types of applications, the AIM standard was developed as part of the Cancer Bioinformatics Grid project of the National Institutes of Health (40,41).…”

Section: Aim Standardmentioning

confidence: 99%

Ontology-based Image Navigation: Exploring 3.0-T MR Neurography of the Brachial Plexus Using AIM and RadLex

et al. 2015

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“…This presents a unique problem with quality control standards because image findings are typically stored in unstructured text formats or private database schemas and custom or nonstandard lexicons. The AIM project [15][16][17][18] objective is to provide a standardized semantically interoperable information model of image pixel meaning and to provide standardized storage formats such as DICOM, XML, and HL7 Clinical Document Architecture (CDA).…”

Section: Understanding the Problemsmentioning

confidence: 99%