rexcardan/Evil-DICOM 开源项目中文解读：技术栈、适用场景与上手建议

项目介绍

rexcardan/Evil-DICOM 是一个托管在 GitHub 上的开源项目，主要使用 C# 编写，目前获得 193 个 Star、96 次 Fork。

仓库全名: rexcardan/Evil-DICOM

README 摘要

A simple to use C# library for reading and manipulating DICOM files. New documentation added to github via Github pages. Online API via DocFX Dot Net Standard Compliant (multiplatform) MIT Open Source license Examples On GH Pages NuGet packages released with each build 10,000+ downloads Wickedly Simple Read more at the project website at http://rexcardan.github.io/Evil-DICOM/ Content | Link | Introductory Video |…

完整内容见 GitHub 原始 README 或本页。

常见问题

Evil-DICOM 用什么语言开发？

主要使用 C# 编写，目前有 193 个 Star。

如何获取 Evil-DICOM 的源码？

可以直接克隆仓库：git clone https://github.com/rexcardan/Evil-DICOM.git，默认分支为 master；安装与运行步骤见仓库 README。

Evil-DICOM 最近还在维护吗？

仓库最近一次更新为 2024年8月21日，当前有 27 个未关闭 Issue；Star 数为 193，可作为社区活跃度的参考。

关于

A C# DICOM Library

dicom medical-physics radiation-oncology radiology

193 Stars
96 Forks
39 Watching

描述取自 GitHub 官方 API，中文内容由 GitRead 中文社区编辑团队整理。

简要分析

热度分

424

价值分

147

活跃状态

活跃

GitHub

语言占比

CSS

JavaScript

贡献者

ProfoundMedicalDeveloper

jazb83

jmeridth

Logo

A simple to use C# library for reading and manipulating DICOM files. New documentation added to github via Github pages.

Online API via DocFX
Dot Net Standard Compliant (multiplatform)
MIT Open Source license
Examples On GH Pages
NuGet packages released with each build
10,000+ downloads

Wickedly Simple

var dcm = DICOMObject.Read("MyDICOMFile.dcm");
//***COOL CODE GOES HERE***
//Writing is equally easy
dcm.Write("MyHackedDICOMFile.dcm");

Read more at the project website at http://rexcardan.github.io/Evil-DICOM/

Content	Link
Introductory Video	Youtube
Examples	Example Operations
Online API	API Documentation

Evil-DICOM used and featured in publications

Mayo, C., et al., Demonstration of a software design and statistical analysis methodology with application to patient outcomes data sets. Medical physics, 2013. 40(11): p. 111718.
Vickress, J., R. Barnett, and S. Yartsev, Data Inventory for Cancer Patients Receiving Radiotherapy for Outcome Analysis and Modeling. Biomedical Data Mining, 2014. 3(105): p. 2.
Saalfeld, P., et al., Touchless measurement of medical image data for interventional support. Mensch und Computer 2017-Tagungsband, 2017.
Miras, H., et al., Monte Carlo verification of radiotherapy treatments with CloudMC. Radiation Oncology, 2018. 13(1): p. 99.
Patrick Saalfeld, D.K. and C.H. Bernhard Preim, Image Data for Interventional Support. Mensch und Computer 2017-Tagungsband: Spielend einfach interagieren, 2018. 17: p. 83.
Pyyry, E.J. and W. Keranen, Varian APIs: A handbook for programming in the Varian oncology software ecosystem. 2018.
Saalfeld, P., J. Patzschke, and B. Preim, An immersive system for exploring and measuring medical image data. Mensch und Computer 2017-Tagungsband: Spielend einfach interagieren, 2018. 17: p. 73.
Alkhimova, S. and V. Kuleshov, Analysis of turning angle in scope of brain tissue segmentation with CUSUM filter. 2019.
Alkhimova, S. and S. Sliusar, Analysis of effectiveness of thresholding in perfusion ROI detection on T2-weighted MR images with abnormal brain anatomy. arXiv preprint arXiv:1912.05469, 2019.

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