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README.md

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DICOM parser in Go

Build Status GoDoc Reference

This is a (hard-ish) fork of go-dicom--a golang DICOM image parsing library. A command line tool to parse imagery and data out of DICOM files is also included (dicomutil). We have been working on this package with the goal of building a full-featured and high-performance dicom parser with new features and improvements. So far improvements include:

  • parsing and extracting multi-frame DICOM imagery (both encapsulated and native pixel data)
  • exposing a Parser golang interface to make mock-based testing easier for clients
  • Channel-based streaming of frames to a client as they are parsed out of the dicom

We're open to suggestions and comments -- open an issue if you have any.

Usage

To use this in your golang project, simply import our pacakge github.com/gradienthealth/dicom and then you can use our Parser for your parsing needs:

p, err := dicom.NewParserFromFile("myfile.dcm", nil)
opts := dicom.ParseOptions{DropPixelData: true}

element := p.ParseNext(opts) // parse and return the next dicom element
// or
dataset, err := p.Parse(opts) // parse whole dicom

More details about the package can be found in the godoc

CLI Tool

A CLI tool that uses this package to parse imagery and metadata out of DICOMs is provided in the dicomutil package.

Usage

dicomutil --extract-images myfile.dcm

Note: for some dicoms (with native pixel data) no automatic intensity scaling is applied yet (this is coming). You can apply this in your image viewer if needed.

Docker build

To build the tool for all platforms (Mac, Windows, Linux) from source using docker, execute the following in the cloned repo:

docker build . -t godicom
docker run -it -v $PWD/build:/go/src/github.com/gradienthealth/dicom/build godicom make release

You can then use the binaries that will show up in the build folder in your current working directory

Build manually

To build manually, ensure you have make, golang, and dep installed on your machine. Clone (or go get) this repo into your gopath then:

make

Acknowledgements