gonii VS Viewers

Compare gonii vs Viewers and see what are their differences.

gonii

Standalone NIfTI file parser (by okieraised)
medical-imaging nifti-1 nifti-2 nifti-format nifti-gz nifti-images nifti nii
Source Code
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Viewers

OHIF zero-footprint DICOM viewer and oncology specific Lesion Tracker, plus shared extension packages (by OHIF)
nci-itcr nci-qin quantitative-imaging imaging-informatics cancer-imaging-research Dicom image-analysis medical-image-processing medical-imaging ReactJS JavaScript HacktoberFest dicom-viewer Medical
Source Code
docs.ohif.org
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gonii Viewers
1 2
8 2,916
- 1.8%
5.1 9.7
about 1 year ago 6 days ago
Go TypeScript
BSD 3-clause "New" or "Revised" License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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gonii

Posts with mentions or reviews of gonii. We have used some of these posts to build our list of alternatives and similar projects.

Viewers

Posts with mentions or reviews of Viewers. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-21.
  • Show HN: Volume rendering 3D data in Three.js and GLSL
    5 projects | news.ycombinator.com | 21 Apr 2024
    My app does not support DICOM files as input. Just Uint8 256x256x256 raw files that are scaled 1x1x1. Maybe if I had the chance to work on it full-time I'd have the time to add those features, but it's just a side project for now.

    Have you looked into Slicer3D[0] which is a multi-platform desktop app or Open Health Image Foundations dicom viewer[1] which is web-based? Perhaps one of these will help.

    [0] https://www.slicer.org/

    [1] https://github.com/OHIF/Viewers

  • [P] VinDr Lab - an open-source annotation platform for Medical AI
    2 projects | /r/MachineLearning | 2 Apr 2021
    On a side note, I noticed that a significant portion of this viewer is based on work done by folks at OHIF. Because of the incredible amount of work that went into creating those tools, it is worth citing them in the VinDR arxiv paper:

What are some alternatives?

When comparing gonii and Viewers you can also consider the following projects:

nii2dcm - nii2dcm: NIfTI to DICOM creation with Python

cornerstone - JavaScript library to display interactive medical images including but not limited to DICOM

MRIcroGL - v1.2 GLSL volume rendering. Able to view NIfTI, DICOM, MGH, MHD, NRRD, AFNI format images.

vindr-lab - A Data Platform for Medical AI that enables building high-quality datasets and algorithms with lean process and advanced annotation features.

libvips - A fast image processing library with low memory needs.

cornerstone3D - Cornerstone is a set of JavaScript libraries that can be used to build web-based medical imaging applications. It provides a framework to build radiology applications such as the OHIF Viewer.

dcm2niix - dcm2nii DICOM to NIfTI converter: compiled versions available from NITRC

dwv - DICOM Web Viewer: open source zero footprint medical image library.

go2com - A DICOM file parser

dicomviewer - DICOM Viewer in Nextcloud

image-size - Node module for detecting image dimensions

Phantom - Effective DICOM anonymization in Python

gonii vs nii2dcm Viewers vs cornerstone gonii vs MRIcroGL Viewers vs vindr-lab gonii vs libvips Viewers vs cornerstone3D gonii vs dcm2niix Viewers vs dwv gonii vs go2com Viewers vs dicomviewer Viewers vs image-size Viewers vs Phantom