| Title |
Creation of DICOM—Aware Applications Using ImageJ
|
|---|---|
| Published in |
Journal of Digital Imaging, April 2005
|
| DOI | 10.1007/s10278-004-1879-4 |
| Pubmed ID | |
| Authors |
Daniel P. Barboriak, Anthony O. Padua, Gerald E. York, James R. MacFall |
| Abstract |
The demand for image-processing software for radiology applications has been increasing, fueled by advancements in both image-acquisition and image-analysis techniques. The utility of existing image-processing software is often limited by cost, lack of flexibility, and/or specific hardware requirements. In particular, many existing packages cannot directly utilize images formatted using the specifications in part 10 of the DICOM standard ("DICOM images"). We show how image analyses can be performed directly on DICOM images by using ImageJ, a free, Java-based image-processing package (http://rsb.info.nih.gov/ij/). We demonstrate how plug-ins written in our laboratory can be used along with the ImageJ macro script language to create flexible, low-cost, multiplatform image-processing applications that can be directed by information contained in the DICOM image header. |
Mendeley readers
The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 72 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 16% |
| Student > Master | 11 | 15% |
| Student > Ph. D. Student | 8 | 11% |
| Student > Bachelor | 7 | 9% |
| Student > Doctoral Student | 7 | 9% |
| Other | 13 | 18% |
| Unknown | 16 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 24 | 32% |
| Engineering | 8 | 11% |
| Computer Science | 7 | 9% |
| Biochemistry, Genetics and Molecular Biology | 5 | 7% |
| Agricultural and Biological Sciences | 4 | 5% |
| Other | 9 | 12% |
| Unknown | 17 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 February 2016.
All research outputs
#7,453,350
of 22,786,087 outputs
Outputs from Journal of Digital Imaging
#339
of 1,049 outputs
Outputs of similar age
#20,280
of 57,909 outputs
Outputs of similar age from Journal of Digital Imaging
#2
of 5 outputs
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So far Altmetric has tracked 1,049 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 45th percentile – i.e., 45% of its peers scored the same or lower than it.
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