Topic
Image markup
About: Image markup is a research topic. Over the lifetime, 28 publications have been published within this topic receiving 537 citations.
Papers
TL;DR: The AIM information model, schemas, software libraries, and tools are described so as to prepare researchers and developers for their use of AIM.
Abstract: Image annotation and markup are at the core of medical interpretation in both the clinical and the research setting. Digital medical images are managed with the DICOM standard format. While DICOM contains a large amount of meta-data about whom, where, and how the image was acquired, DICOM says little about the content or meaning of the pixel data. An image annotation is the explanatory or descriptive information about the pixel data of an image that is generated by a human or machine observer. An image markup is the graphical symbols placed over the image to depict an annotation. While DICOM is the standard for medical image acquisition, manipulation, transmission, storage, and display, there are no standards for image annotation and markup. Many systems expect annotation to be reported verbally, while markups are stored in graphical overlays or proprietary formats. This makes it difficult to extract and compute with both of them. The goal of the Annotation and Image Markup (AIM) project is to develop a mechanism, for modeling, capturing, and serializing image annotation and markup data that can be adopted as a standard by the medical imaging community. The AIM project produces both human- and machine-readable artifacts. This paper describes the AIM information model, schemas, software libraries, and tools so as to prepare researchers and developers for their use of AIM.
114 citations
Patent•
19 Nov 1991TL;DR: In this paper, an image markup detection device and method identifies and extracts markup lines and regions marked automatically or interactively by a user with an ordinary pen or pencil using morphological image processing operations on a scanned source image.
Abstract: An image markup detection device and method identifies and extracts markup lines and regions marked automatically or interactively by a user with an ordinary pen or pencil Only morphological image processing operations on a scanned source image are used, resulting in the extrapolation of markup lines and marked region The markup lines are either extracted from the image, or the background information of the image (eg, text) is removed, leaving only the markup lines The marked region can then be printed, transferred or otherwise processed
55 citations
TL;DR: A structured reporting work flow has been developed that allows quantitative data created at an advanced imaging workstation to be seamlessly integrated into the radiology report with minimal radiologist intervention.
Abstract: Quantitative and descriptive imaging data are a vital component of the radiology report and are frequently of paramount importance to the ordering physician. Unfortunately, current methods of recording these data in the report are both inefficient and error prone. In addition, the free-text, unstructured format of a radiology report makes aggregate analysis of data from multiple reports difficult or even impossible without manual intervention. A structured reporting work flow has been developed that allows quantitative data created at an advanced imaging workstation to be seamlessly integrated into the radiology report with minimal radiologist intervention. As an intermediary step between the workstation and the reporting software, quantitative and descriptive data are converted into an extensible markup language (XML) file in a standardized format specified by the Annotation and Image Markup (AIM) project of the National Institutes of Health Cancer Biomedical Informatics Grid. The AIM standard was created to allow image annotation data to be stored in a uniform machine-readable format. These XML files containing imaging data can also be stored on a local database for data mining and analysis. This structured work flow solution has the potential to improve radiologist efficiency, reduce errors, and facilitate storage of quantitative and descriptive imaging data for research.
41 citations
Proceedings Article•
1 Jan 2001TL;DR: A prototype system of open source tools implementing an authoring system, a client system, and an image annotation database which can be queried though the Web is developed.
Abstract: Image Markup Language is an extensible markup language (XML) schema used to describe both image metadata and annotations. It describes both data pertaining to an entire image, and data that are tied to specific regions or features of the image. Developed for a specific domain in Medical Education, this pa-per describes extensions to take advantage of the Dublin Core metadata standard, and of an XML schema for vector graphics representation. We have developed a prototype system of open source tools implementing an authoring system, a client system, and an image annotation database which can be queried though the Web.
24 citations
TL;DR: The utility of the Annotation and Image Markup standard in a World Wide Web-based application that was developed to automatically summarize prior and current quantitative imaging measurements is demonstrated and could enhance quantitative imaging in clinical practice without adversely affecting the current work flow.
Abstract: A Web-based application that uses the Annotation and Image Markup standard was developed to provide an automated means for radiologists to review the results of prior imaging studies, analyze quantitative imaging results over time, and evaluate alternative quantitative disease response metrics.
19 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2020 | 1 |
| 2017 | 1 |
| 2014 | 3 |
| 2013 | 1 |
| 2012 | 4 |
| 2011 | 3 |