Fiji/Unet 2016

Introduction

U-Net is a plugin for ImageJ. It is a generic deep-learning solution for frequently occurring quantificationtasks like cell detection and shape measurements in biomedical image data. In this case, Unet is built on Fiji, a distribution for ImageJ, specifically build to facilitate scientific image analysis.¹
Unet works with and is dependent of a modified version of caffe: caffe_unet.

Installed version(s)

This version is installed and currently available on environment hpc-uniol-env:

caffe_unet/99bd99795d-intel-2016b-Python-2.7.12

Using Fiji/Unet

To use Fiji, you need to have a bash session enabled which forwards X11, especially if you depend on the programs GUI. (For more about this you can consult our login manual)

If you just want to work with Fiji without GPU support, you can load the module and straight ahead start the program:

module load hpc-uniol-env
module load fiji
fiji-linux64

Should you need to work with GPUs, you will have to do some preparations:

Documentation

The full documentation can be found [ here].