SuRVoS2 is an open-source and user-friendly collection of tools which accelerate annotation and segmentation of large volumetric datasets. It enables either shallow or deep machine learning approaches, using a suite of image processing filters, supervoxels (boundary adherent groupings of similar, adjacent voxels), and annotation hierarchies. SuRVoS2 also provides tools for visualisation and interaction with large numbers of distributed annotations (e.g., those performed by multiple members of a group or citizen scientists). This application has been implemented both as a napari plugin and as an API for generic programming usage.

The workshop will demonstrate basic usage of our annotation and segmentation workflows, and guide participants through applying SuRVoS2 to their own datasets. Participants with their own datasets should prepare their images as single stacks of tiff or hdf5 images cropped to their region-of-interest, otherwise, example datasets will be provided. No image segmentation or programming experience is required to participate in this workshop.

For more information, please see https://linktr.ee/survos

This workshop will focus and highlight how IPSDK Explorer can help you in processing your images and volumes in an easy and efficient way.

This session will be proposed as an hands-on session, where you will
- Use IPSDK Explorer Automatic Python Script generator to create Python scripts and workflows without needing any Python skills
- Use IPSDK Machine Learning modules
o Smart Segmentation
o Smart Classification
- Discover IPSDK latest features
o Adaptive watershed to overpass the watershed limitations
o Enhance your acquisition using the Local Contrast Enhancement feature
o Machine Learning SuperPixel / SuperVoxel module

In this course we will be covering the basics of X-Ray CT acquisition and reconstruction. We will introduce the filtered back projection (FBP) algorithm and the cone beam variant (FDK), which are the most widely used algorithms for reconstruction of XCT data. We will discuss the family of iterative reconstruction algorithms with regularisation that can be employed when FBP/FDK do not lead to satisfactory results.

The course will make use of the Core Imaging Library (CIL), an open-source Python framework for tomographic imaging, developed by the Collaborative Computational Project in Tomographic Imaging (CCPi) and available from https://www.ccpi.ac.uk/cil. CIL provides FBP/FDK, state-of-the-art iterative reconstruction algorithms, pre-processing and visualization tools as well as readers for some of the common micro-CT data formats. The course will make use of an online platform where all the relevant software and data is pre-installed, but details on how to install CIL will be provided.
In this three-hour hands-on training course you will
• learn to load in and process micro-CT data (e.g. Nikon and Zeiss),
• produce and display your very own reconstructions using CIL,
• appreciate the pros and cons of iterative reconstruction when compared to filtered back-projection,
• experiment with different iterative reconstruction algorithms.

In this workshop, we will demonstrate how Thermo Scientific Avizo Software via advanced visualization and image processing techniques can enable a better understanding from various types of samples. By going through workflows on CT data from Life Sciences and Material Sciences examples, we will provide hands-on opportunity to have an insight of the recently added capabilities which are built in the software (visualization, advanced segmentation, fiber reconstruction, porosity analysis, animation of your results).
The workshop will demonstrate:
- How to load and visualize CT data
- How to use a combination of interactive and algorithm based tools for segmentation
- How to use the fiber tracing solution
- How to easily animate your results and produce attractive movies from your data

SuRVoS2 is an open-source and user-friendly collection of tools which accelerate annotation and segmentation of large volumetric datasets. It enables either shallow or deep machine learning approaches, using a suite of image processing filters, supervoxels (boundary adherent groupings of similar, adjacent voxels), and annotation hierarchies. SuRVoS2 also provides tools for visualisation and interaction with large numbers of distributed annotations (e.g., those performed by multiple members of a group or citizen scientists). This application has been implemented both as a napari plugin and as an API for generic programming usage.

The workshop will demonstrate basic usage of our annotation and segmentation workflows, and guide participants through applying SuRVoS2 to their own datasets. Participants with their own datasets should prepare their images as single stacks of tiff or hdf5 images cropped to their region-of-interest, otherwise, example datasets will be provided. No image segmentation or programming experience is required to participate in this workshop.

For more information, please see https://linktr.ee/survos

This workshop will focus and highlight how IPSDK Explorer can help you in processing your images and volumes in an easy and efficient way.

This session will be proposed as an hands-on session, where you will
- Use IPSDK Explorer Automatic Python Script generator to create Python scripts and workflows without needing any Python skills
- Use IPSDK Machine Learning modules
o Smart Segmentation
o Smart Classification
- Discover IPSDK latest features
o Adaptive watershed to overpass the watershed limitations
o Enhance your acquisition using the Local Contrast Enhancement feature
o Machine Learning SuperPixel / SuperVoxel module

In this course we will be covering the basics of X-Ray CT acquisition and reconstruction. We will introduce the filtered back projection (FBP) algorithm and the cone beam variant (FDK), which are the most widely used algorithms for reconstruction of XCT data. We will discuss the family of iterative reconstruction algorithms with regularisation that can be employed when FBP/FDK do not lead to satisfactory results.

The course will make use of the Core Imaging Library (CIL), an open-source Python framework for tomographic imaging, developed by the Collaborative Computational Project in Tomographic Imaging (CCPi) and available from https://www.ccpi.ac.uk/cil. CIL provides FBP/FDK, state-of-the-art iterative reconstruction algorithms, pre-processing and visualization tools as well as readers for some of the common micro-CT data formats. The course will make use of an online platform where all the relevant software and data is pre-installed, but details on how to install CIL will be provided.
In this three-hour hands-on training course you will
• learn to load in and process micro-CT data (e.g. Nikon and Zeiss),
• produce and display your very own reconstructions using CIL,
• appreciate the pros and cons of iterative reconstruction when compared to filtered back-projection,
• experiment with different iterative reconstruction algorithms.

In this workshop, we will demonstrate how Thermo Scientific Avizo Software via advanced visualization and image processing techniques can enable a better understanding from various types of samples. By going through workflows on CT data from Life Sciences and Material Sciences examples, we will provide hands-on opportunity to have an insight of the recently added capabilities which are built in the software (visualization, advanced segmentation, fiber reconstruction, porosity analysis, animation of your results).
The workshop will demonstrate
- How to load and visualize CT data
- How to use a combination of interactive and algorithm based tools for segmentation
- How to use the fiber tracing solution
- How to easily animate your results and produce attractive movies from your data