Home < Slicer3.2:Training

Welcome to the 3D Slicer3.2 User Training 101

The information on this page applies to 3D Slicer version 3. If you are looking for materials about Slicer version 2, please visit the Slicer2 101 page.

Slicer 3 has been designed as
- an easy-to-use application for 3D image analysis and visualization,
- an open-source environment for software development,
- a technology delivery platform for community breakthroughs.
Slicer3 is distributed under a BSD open source license, and is designed to enable a collaborative development environment.
This page contains training materials and data sets for self-guided training in the use of Slicer3

For questions about the materials on this page, please send an e-mail to Sonia Pujol, Ph.D. (spujol at bwh.harvard.edu).

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Software Installation

The Slicer download page contains links for downloading the different versions of Slicer 3.

Training Compendium

Category	Tutorial	Sample Data	Image
1.1	Data Loading and 3D Visualization in Slicer3	SlicerSampleVisualization.tar.gz SlicerSampleVisualization.zip‎
1.2	Manual segmentation with 3D Slicer
1.3	EM Segmentation Course Background Materials: EMSegmenter History	AutomaticSegmentation.tar.gz ‎AutomaticSegmentation.zip
1.4	Affine and Deformable Registration in Slicer 3	SlicerSampleRegistration.tgz SlicerSampleRegistration.zip
1.5	Processing of Diffusion Weighted Imaging and Diffusion Tensor Imaging data in Slicer3 Background Materials:DT-MRI module.	Slicer3DiffusionTutorialData.zip
1.6	Detecting subtle change in pathology This tutorial consists of two MR scans of a patient with meningioma.	ChangeTracker-Tutorial-Data.zip
1.7	Detecting white matter lesions in lupus This tutorial consists of five MR scans of patients with lupus.	Lupus-Tutorial-Data.tgz ‎ Lupus_Tutorial_Data.zip
1.8	FreeSurfer Course This tutorial teaches how to visualize FreeSurfer segmentations and parcellation maps of the brain.	FreeSurfer Tutorial Data FreeSurferTutorialData.zip
2.1	Programming into Slicer3 This tutorial is intended for engineers and scientists who want to integrate stand-alone programs outside of the Slicer3 source tree.	HelloWorld_Plugin.zip
2.2	Image Guided Therapy Planning Tutorial This tutorial takes the trainee through a complete workup for neurosurgical patient specific mapping.See pages 58 to 80 of this tutorial on using the "Simple region growing" segmentation module. Background Materials: Neurosurgical Planning.	NeurosurgicalPlanningTutorialData.zip
3.1	Slicer3 as a research tool for image guided therapy research (IGT) This tutorial is intended for engineers and scientists who want to use Slicer 3 for IGT research.
3.2	SPL-PNL Brain Atlas Tutorial This three-dimensional brain atlas dataset, derived from a volumetric, whole-head MRI scan, contains the original MRI-scan, a complete set of label maps, three-dimensional reconstructions (200+ structures) and a tutorial. Background Materials: SPL-PNL Brain Atlas.	SPL-PNL Brain Atlas
3.3	SPL Abdominal Atlas Tutorial This three-dimensional abdominal atlas was derived from a computed tomography (CT) scan, using semi-automated image segmentation and three-dimensional reconstruction techniques. The dataset contains the original CT scan, detailed label maps, three-dimensional reconstructions and a tutorial. Background Materials: SPL Abdominal Atlas.	SPL Abdominal Atlas
3.4	Using XNAT Desktop and Slicer3 for remote data handling This tutorial is intended for researchers who wish to upload local datasets to a remote XNAT repository like XNAT Central and retrieve catalog files that can be opened inside Slicer.
3.5	Harnessing Grid Computational Resources and integration with Slicer through the Grid Wizard Enterprise system These tutorials are intended for researchers who wish to utilize distributed computational resources. GWE Basic Tutorial GWE Basic Tutorial Using Web Control Panel GWE Advanced Tutorial GSlicer3 Tutorial	Grid Wizard Enterprise GWE Information GWE Installation Guide GWE Configuration Guide End Users Guide GSlicer3 Guide issue tracking system mailing lists	Featured Study Case (YouTube)