What is CDeep3M Our goal is improve reproducibility and to make deep-learning algorithms available to the community, we built CDeep3M as a cloud-based tool for image segmentation tasks, using the underlying architecture of a state-of-the-art deep-learning convolutional neural network (CNN), DeepEM3D7, which was integrated in the Caffe deep-learning framework.


Upload trained model

Upload your trained CDeep3M model/s and share it to contribute to the database. Each trained model receives a DOI for citations.
(Info: Follow these steps to generate a new trained model or re-train a previously trained model)

CDeep3M Preview (import test images)

Upload own images and try the CDeep3M preview function. Select a trained model from the database, augspeed, and frames to run CDeep3M remotely (using the PRP cluster).

CDeep3M Demo (CIL image volumes)

Browse through large SBEM volumes hosted on the CIL, select ROI for segmentation and run CDeep3M Demo to test a trained model from the database on the image volume.