CODEWITHSUNDEEP
deep-learningcomputer-visionimage-segmentationmedical
Sai
Sai

Reputation: 127

NIfTi vs DICOM for 3D volumetric data

Are there major benefits of selecting NIfTi over DICOM (or viz.) as the choice of data format? I am working on 3D Volumetric semantic segmentation. I will have to convert either format to numpy array or tensor before feeding to the network, but curious on the performance benefits of selection.

Upvotes: 2

Views: 3077

Answers (1)

gavinb
gavinb

Reputation: 20048

(This question risks being opinion-based, so trying to stick to facts.)

DICOM is a very powerful, flexible but complex format, and its strength is to provide interoperability between different hardware and software. However, DICOM is not particularly efficient for image processing and analysis. One potential drawback of DICOM is that a single volume is stored as a sequence of 2D slices, which can be cumbersome to deal with.

NIfTi is an improved version of the Analyze file format, which was designed to be simpler than DICOM, while still retaining all the essential metadata. And it has the added benefit of being able to store a volume in a single file, with a simple header followed by raw data. This makes it fast to load and process.

There are several other medical file formats suitable for this task. You may also wish to consider NRRD which has many features in common with NIfTi. Simple format, fast to parse and load, flexible storage encoding for 2,3,4D data. Many tools and libraries can process NRRD files too.

So given your primary need is for efficient storage and analysis, NIfTi or NRRD would be a better choice.

Upvotes: 4

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