Component

The napari-pyclesperanto-assistant is a yet experimental napari plugin for building GPU-accelerated image processing workflows targeting life-sciences and bio-image analysis. It is part of the clEsperanto project. It uses pyclesperanto and pyopencl as backend for processing images.

AnnotatorJ is a Fiji Plugin to ease annotation of images, particulrly useful for Deep Learning or to validate an alogorithm. Interestingly, it allows annotation for instance segmentation, semantic segmentation, or bounding box annotations. It includes toolssuch as active contours to ease these annotations.

Machine Learning made easy

APEER ML provides an easy way to train your own machine learning
models and segment your microscopy images. No expertise or coding required.

This Fiji plugin is a python script for CLEM registration using deep learning, but it could be applied in principle to other modalities. The pretrained model was learned on chromatin SEM images and fluorescent staining, but a script is also provided to train an new model, based on CSBDeep. The registration is then performed as a feature based registration, using register virtual stack plugin (which extract features and then perform RANSAc. Editing the script in python gives access to more option (such as the transformation model to be used, similarity by default. Images need to be prepared such that they contain only one channel, but channel of ineterst (to be transformed with the same transformation) can be given as input, and Transform Virtual Stack plugin can be used as well.