Java

SimpleITK provides a simplified interface to ITK in a variety of languages. A user can either download pre-built binaries, if they are available for the desired platform and language, or SimpleITK can be built from the source code. Currently, Python binaries are available on Microsoft Windows, GNU Linux and Mac OS X. C# and Java binaries are available for Windows. We are also working towards supporting R packaging.

ZEN and APEER – Open Ecosystem for integrated Machine-Learning Workflows

Open ecosystem for integrated machine-learning workflows to train and use machine-learning models for image processing and image analysis inside the ZEN software or on the APEER cloud-based platform

Highlights ZEN

• Simple User Interface for Labeling and Training
• Engineered Features Sets and Deep Feature Extraction + Random Forrest for Semantic Segmentation
• Object Classification workflows
• Probability Thresholds and Conditional Random Fields
• Import your own trained models as *.czann files (see: czmodel · PyPI)
• Import "AIModel Containes" from arivis AI for advanced Instance Segmentation
• Integration into ZEN Measurement Framework
• Support for Multi-dimensional Datasets and Tile Images
• open and standardized format to store trained models

ZEN Intellesis Segmentation

ZEN Intellesis - Pretrained Networks

Intellesis Object Classification

Highlights Aarivis AI

• Web-based tool to label datasets to train Deep Neural Networks
• Fully automated hyper-parameter tuning
• Export of trained models for semantic segmentation and AIModelContainer for Instance Segmentation

Annotation Tool

R wrapper around the OMERO Java Gateway, to enable access to OMERO via R using rJava

OpenImadis stands for Open Image Discovery: A platform for Image Life Cycle Management. It was previously called CID iManage (for Curie Image Database).

No image data conversions, no duplication.

- Uploads data to a secure server in the original format

- Unique id for data

Supports sharing and collaboration with access control

- Allows users to upload, view, update or download data based on their access privileges

Supports multiple ways of attaching meta-information

- Annotations, comments and file attachments

-Analysis results as query-able visual objects

Supports Archiving (data moving to another long-term storage but still searchable)

Facilitates custom visualization and analysis

- Access data from preferred analysis and visualization tools

- Access relevant bits of data to build efficient web and mobile application

Facilitate easy access to analysis and visualization applications hosted on other servers

- Run analysis on dedicated compute clusters

- Access applications hosted and published by other users

Highly Scalable

- Supports on-the-fly addition of server nodes to scale concurrent usage

A collection of components for super resolution image data:

• Detect Molecules
• Reconstruct Image
• Results table
• Drift correction
• Chromatic correction