Free 3D software

 
Fiji (is just ImageJ) https://fiji.sc/
Your best friend for general image manipulation (e.g. cropping, adjusting, and orienting image stacks), editing, and basic analysis. Many many plugins to do almost anything, some quite sophisticated. Open-source, easy multi-language scripting.

Dragonfly https://dragonfly.comet.tech/
Dragonfly is my current top choice as a free replacement for Amira/Avizo. Free for non-commercial research (license on request), well-documented and extensively used, easy to get started with video tutorials. Many of the manual segmentation tools also work directly in the 3D view. Includes a convolutional neural networks Deep Learning based tools for complex segmentation. Windows and Linux only. 

Drishti https://github.com/nci/drishti
Can make amazing visualizations, including key-frames-based animations. Powerful segmentation editor (DrishtiPaint). Steep initial learning curve, but the online tutorials are helpful. Drishti Prayog (https://github.com/nci/drishti#drishti-prayog ) makes spectacular interactive touch-screen presentations.

3D Slicer https://www.slicer.org/
An "open source software platform for medical image informatics, image processing, and three-dimensional visualization...built over two decades through support from the National Institutes of Health and a worldwide developer community.” Well-developed and widely used, with extensive documentation and training tutorials. Reasonably easy to get started. 

SlicerMorph is a Slicer extension with extensive tools for 3D analysis and morphometrics (https://github.com/SlicerMorph).

Tomviz https://tomviz.org/
A "cross platform, open source application for the processing, visualization, and analysis of 3D tomographic data. Here the full pipeline of data processing steps from reconstruction to visualization to analysis of 3D data can be presented, saved, and restored." https://tomviz.readthedocs.io/en/latest/visualization/

ITK-SNAP http://www.itksnap.org/pmwiki/pmwiki.php 
 Designed for 3D image segmentation, "emphasizes interaction and ease of use, with the bulk of the development effort dedicated to the user interface."

Microscopy Image Browser http://mib.helsinki.fi/index.html 
A "high-performance Matlab-based software package for advanced image processing, segmentation and visualization of multi-dimensional (2D-4D) light and electron microscopy datasets."

napari https://napari.org/stable/index.html  
 A "fast, interactive viewer for multi-dimensional images in Python is a fast, interactive, multi-dimensional image viewer, with a vibrant plugin ecosystem that expands its capability to tackle various domain-specific visualization and analysis needs." Open source.

InVesalius is a free package for reconstruction of CT and MRI images. Can import DICOM or Analyze files, export files to the STL, OBJ, and PLY formats. Volume rendering, and manual or semi-automatic image segmentation. Win, Linux, Mac.
https://invesalius.github.io/ 

ImageVis3D is a new volume rendering program developed by the NIH/NIGMS Center for Integrative Biomedical Computing (CIBC). The main design goals of ImageVis3D are: simplicity, scalability, and interactivity.  https://sci.utah.edu/software/

Seg3D is a volume segmentation and processing tool developed by the NIH Center for Integrative Biomedical Computing. It combines a flexible manual segmentation interface with powerful higher-dimensional image processing and segmentation algorithms from the Insight Toolkit. It has a strong emphasis on manual and semi-manual segmentation, where filtered data guides the user in making decent segmentations of the data. The program is mainly intended for, but is not strictly limited to, segmentation of biological/medical data. BioMesh3D (part of SCIRun) can be used to turn segmentations into quality meshes which can be used to simulate biological processes on the segmented images. https://sci.utah.edu/software/

ilastik https://www.ilastik.org/ 
"ilastik is a simple, user-friendly tool for interactive image classification, segmentation and analysis.... has workflows for automated (supervised) pixel- and object-level classification, automated and semi-automated object tracking, semi-automated segmentation and object counting without detection."

CDeep3M is a containerized tool, using deep learning for large-scale image segmentation tasks. It is an open source development and the software is free to use. You can run CDeep3M on your local platforms, on cloud providers, on GPU clusters or with free GPU resources on this website. https://cdeep3m.crbs.ucsd.edu/cdeep3m

MeVisLab https://www.mevislab.de/  
A "powerful, modular framework for image processing research and development with a special focus on medical imaging."

MeshLab http://www.meshlab.net/   
Famous freeware for working with surfaces. 


The Scientific Community Image Forum at https://forum.image.sc/ is a discussion site for software-oriented aspects of scientific imaging, particularly (but not limited to) image analysis, processing, acquisition, storage, and management of digital scientific images.

Fiji plugin to open Xradia microCT files

XRM Reader https://doi.org/10.5281/zenodo.7124262

This is a java plugin for Fiji (ImageJ) that reads an *.xrm, *.txrm, or *.txm image file from Xradia microCT systems (in their proprietary format, a form of OLE container) and opens it as an image stack, along with a text window displaying some metadata parameters. The latest version sets the voxel size for the ImageJ stack using the value from the Xradia file. 

To add the plugin to Fiji, download and extract the .zip folder and just drop the two jar files (poi-3.7.jar and XRM_Reader.jar) one at a time onto the Fiji main window. The program should put them in the right places. Restart Fiji and you should find it under Plugins > XRM Reader. If not, manually place poi-3.7.jar in Fiji.app/jars, and the XRM_Reader.jar in Fiji.app/plugins, then restart Fiji.

This code is publicly available and free for anyone to use. If you use it in a publication, please cite the Zenodo doi above. Current versions can also be found here:

https://ucloud.univie.ac.at/index.php/s/RSJ05Nb9FTViCVK

(I modified the above plugin from this one: https://github.com/mrsutherland/XRM_Reader/releases by mrsutherland, 14 Nov 2017)

Macro to make thumbnails for all your XRM files 

I have also included an ImageJ macro (XRM_files_thumbnails.ijm) that makes a preview image (PNG) and metadata file (.txt) with the same filename base as each unpreviewable *.xrm, *.txrm, or *.txm image file (examples below). This is very useful for quickly looking over your stored scans and seeing what each Xradia file contains.

It is possible to select single files, multiple files, or combinations of files and folders as inputs. You can choose whether the script automatically processes every Xradia-format image in all subdirectories, and whether it will skip files that already have .txt and .png file with the same base file name (i.e. Xradia files already processed by this macro).

This is in the ImageJ macro language and requires the XRM Thumbnails plugin, also included in the same archive. This plugin isn't meant to be run on its own, so I like to put XRM_Thumbnails.jar in the folder Fiji.app/plugins/Utilities, so that it does not appear in the Plugins menu, where it is confusing to see next to the XRM Reader plugin.

I like to put the .ijm macro in either Fiji.app/plugins/Scripts/File or Fiji.app/scripts/File, and then it appears in the File pull-down menu.

The macro makes an XYZ montage for each reconstructed stack and a 0° & 90° mugshot for each projection series (really first and middle projections – for a 360° scan it will be front and back images; my machine doesn't do full rotations). It now includes the date/time from .txrm files. (Fun fact: the container files *.xrm, *.txrm, or *.txm can be extracted to a bunch of hex files using 7‑Zip. I opened some of these with Hex Fiend or HxD to get the format of the date entry.)

If you have questions or comments, feel free to contact me.

Brian Metscher

Vienna, Mar. 2026

brian.metscher[at]univie.ac.at

 

>> Note that Xradia .txm files can also be opened directly in Amira 6.4 and higher (Windows), and also in Drishti (https://github.com/nci/drishti). (Also in ORS Dragonfly Pro, but not in the free Dragonfly version.)

TXM-Wizard by fmeirer, liuyijin can open Xradia files also:

https://sourceforge.net/projects/txm-wizard/

https://pubmed.ncbi.nlm.nih.gov/22338691/

>> Real progress toward a Python solution can be found here: https://pypi.org/project/xrmreader/

It's based on the dxchange Python code, which seems to cover the reading of the xrm container files better than the Java parser: https://github.com/data-exchange/dxchange

 

Sample outputs from the preview macro XRM_files_thumbnails.ijm: