Annotation of 3D images is time-consuming and tricky when performed in a 2D plane. This can be a daunting task because each organelle must be annotated accurately in multiple planes. Arivis has published a workflow for machine learning segmentation that uses Arivis VisionVR to annotate organelles in electron microscopy images. Using virtual reality, the user can use stereoscopic vision to perform and refine their annotations in 3D. Then, the seamless integration of Arivis VisionVR and Arivis Vision4D means that the new annotation can be accessed and analysed immediately in Arivis Vision4D.
The incorporation of Arivis VisionVR into the workflow (left image) improves the overall result as the organelles can be annotated much more precisely than if only 2D images were used for the segmentation (right image).
The published workflow can be accessed at this link.
