https://github.com/gradienthealth/dicom

High Performance DICOM Medical Image Parser in Go.
https://github.com/gradienthealth/dicom

dicom dicom-images golang golang-package image medical medical-imaging pacs parser reader

Last synced: 10 days ago
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High Performance DICOM Medical Image Parser in Go.

• Host: GitHub
• URL: https://github.com/gradienthealth/dicom
• Owner: gradienthealth
• License: mit
• Created: 2018-06-20T21:57:38.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2019-07-16T20:18:27.000Z (over 5 years ago)
• Last Synced: 2024-06-18T21:51:21.680Z (8 months ago)
• Topics: dicom, dicom-images, golang, golang-package, image, medical, medical-imaging, pacs, parser, reader
• Language: Go
• Homepage:
• Size: 25.5 MB
• Stars: 79
• Watchers: 7
• Forks: 10
• Open Issues: 20
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# DICOM parser in Go

[![Build Status](https://travis-ci.org/gradienthealth/dicom.svg?branch=master)](https://travis-ci.org/gradienthealth/dicom)

[![GoDoc Reference](https://godoc.org/github.com/gradienthealth/dicom?status.svg)](https://godoc.org/github.com/gradienthealth/dicom)

This is a (hard-ish) fork of [go-dicom](https://github.com/gillesdemey/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:

```go 

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](https://godoc.org/github.com/gradienthealth/dicom)

## 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:

```bash

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](https://github.com/golang/dep) installed on your machine. Clone (or `go get`) this repo into your gopath then:

```

make

```

## Acknowledgements

* Original [go-dicom](https://github.com/gillesdemey/go-dicom)

* Grailbio [go-dicom](https://github.com/grailbio/go-dicom) -- commits from their fork were applied to ours

* Innolitics [DICOM browser](https://dicom.innolitics.com/ciods)

* [DICOM Specification](http://dicom.nema.org/medical/dicom/current/output/pdf/part05.pdf)