Maybe ITK-Snap could be for you, it's free software and cross-platform:

http://www.itksnap.org/pmwiki/pmwiki.php

Best

Gert

Maybe ITK-Snap could be for you, it's free software and cross-platform:

http://www.itksnap.org/pmwiki/pmwiki.php

Best

Gert

ImageJ with plugins would be sufficient. If you need to find all plugins at one place, you may try http://fiji.sc also known as ImageJ2

http://rsb.info.nih.gov/ij/

ParaView is a good option.

Thank you for the reply. Other suggestions are welcome.

Another vote for ImageJ/Fiji. You may also want to consider OsiriX (http://www.osirix-viewer.com)

Thank you Bryan. I think that ImageJ/Fiji is a good option. When it comes to Osirix, unfortunately it isn't a cross-platform solution

A good cross platform solution for medical image analysis is MIPAV, a project supported by the National Institues of Health in the US. Its a JAVA application so can run on most operating system with the support of a java installation. The program is freely available at http://mipav.cit.nih.gov/ . It is built to provide common cross platform analysis tools for groups of researchers.

http://mipav.cit.nih.gov/

I agree with Gert ITK Snap (http://www.itksnap.org/pmwiki/pmwiki.php) is a very simple, but a very user friendly tool for 3D segmentation.

3D slicer (http://www.slicer.org/) is also a quite handy tool, but more complicated for a novice user, because it is equipped with various other functionalities for IGT>

I  did  this  annnotation  using  'paint.'  Is  this  the  kind  of   thing  you  want?

We have developed tools for annotating (segmenting, labeling) MRI brain scans.  It's not easy to use but once trained, you can crank out the annotations.  If you want fast and accurate results, our approach is to write scripts and customize the software to it is very efficient.  We can annotate anything that is visible in 3D medical images.

(I know this thread is old, but maybe somebody is still looking).

Andy.

I'd suggest to try Labelbox (www.labelbox.io).

Labelbox is a cloud based tool to easily label data.

Labelbox makes it really easy to do basic image classification or segmentation tasks.

Relevant for this question, you can easily create a medical data labeling viewer with an open source DICOM viewer and install it in Labelbox to label the large dataset easily among a team of labelers.

You can see their template code here: https://github.com/Labelbox/Labelbox

Additional feature includes project management, team management and performance metrics.

You can try DataTurks [https://dataturks.com/], they provide polygon bounding and bounding boxes. On top of that, its free to use for academic research purpose.

Check some projects here:

https://dataturks.com/projects/trending

Conference Paper Semantic Annotation of Medical Images

http://aircconline.com/ijaia/V4N3/4313ijaia05.pdf

http://www.cs.binghamton.edu/~forweb/publications/yao.pdf

https://web.stanford.edu/group/rubinlab/pubs/18.4.rubin.pdf

Our Mac OS X app RectLabel was cited by the paper below.

Faster R-CNN-Based Glomerular Detection in Multistained Human Whole Slide Images

http://www.mdpi.com/2313-433X/4/7/91/pdf

Semi automatic medical image annotation via active learning

Article Computer-Aided Medical Image Annotation: Preliminary Results...

A useful article in this regard:

Chapter Annotating Medical Image Data