# Extracting Header information from DICOM image

**URL:** https://discourse.itk.org/t/extracting-header-information-from-dicom-image/2187
**Category:** Beginner Questions
**Created:** [August 21, 2019, 8:18pm UTC](https://discourse.itk.org/t/extracting-header-information-from-dicom-image/2187 "2019-08-21T20:18:11Z")
**Posts on this page:** 1
**Showing post:** 10

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### Author: ![pieper](https://discourse.itk.org/user_avatar/discourse.itk.org/pieper/32/22_2.png) [@pieper](https://discourse.itk.org/u/pieper)
#### Post date: [September 3, 2019, 7:17pm UTC](https://discourse.itk.org/t/extracting-header-information-from-dicom-image/2187/10 "2019-09-03T19:17:57Z")

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Right - dicomParser is more general, since it is generally speaking slice-oriented and allows you to have various image stacks. I’m not sure how daikon handles that. In OHIF the patient/study/series organization comes for free if the data comes via dicomweb.

In dcmjs, I have been using the [concept of modality-specific code](https://github.com/dcmjs-org/dcmjs/blob/master/src/normalizers.js) to normalize acquisitions into image volumes. IMHO this is the right way to organize frames into volumes or sequences for rendering or processing because modality-specific code can be adapted to make better use of the acquisition-specific data. This is something like the dicom plugins we use in Slicer to map various dicom datasets to the corresponding Slicer data nodes.

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