Version 3.0 integrates the deep learning framework Tensorflow for object detection. You can use a pre-trained model, like our glomeruli detection model available in our model zoo, or train your own deep learning model based on manually created object annotations. This new feature allows to detect arbitrary complex and heterogeneous objects like glomeruli, vessels, and[…]
The new Orbit version 2.8 comes with a brand new masking functionality. It allows you to define ‘active region’ classes within a classification model or use a segmentation model to define the segmented objects as ‘active’ and then do another classification or segmentation inside these active regions. This functionality unveils the power of Orbit for[…]
Orbit 2.7 has build-in support for native NDPI(s) reading out of the box (Win and Linux distributions). This leads to a tremendous speed improvement for reading NDPI and NDPIS files from local file system. We want to thank Hamamatsu for the great support and for providing the native library.
Segmenting cells in cell clusters is very challenging because they cannot be separated easily from the background – thus classical segmentation algorithms fail. Unfortunately in WSI (whole slide imaging) you will have to deal with these situations – especially if you don’t have a single cell layer, like e.g. in tumor tissue. A collaboration with[…]
Today we release Orbit version 2.52 (for Omero 5.2.x) and Orbit 2.53 (for Omero 5.3.x). Both versions are identical except support for different Omero major versions and support multichannel / fluorescence images with unlimited number of channels. In addition, this version provides many bugfixes and speed improvements. Multi series / scenes can be selected in[…]
Orbit 2.4.3 makes use of the new Bio-Formats 5.3.0 library which enables CZI files with JPEG-XR compression support. In addition Orbit supports multi image series, e.g. you can open all image series of your VSI images.
Today the new Orbit version 2.41 is released. The main achievement of this major version is the ability to work with whole slide images images in standalone mode, even without using an image server. In addition, many speed improvements (faster rendering) and bug-fixes are included. Orbit is designed to work with an image server, e.g.[…]
Orbit Image Analysis and all its dependencies are now available via Maven Central. If you want to use the Orbit API, just add <dependency> <groupId>com.actelion.research</groupId> <artifactId>orbit-image-analysis</artifactId> <version>2.30</version> </dependency> in your POM or compile ‘com.actelion.research:orbit-image-analysis:2.30’ for Gradle. See the Orbit API page for details.