HarmonicNet

This repository contains code used for the Spherical Harmonics-based 3D cell segmentation proposed in Paper, Preprint.

If you use this code, please cite:
D. Eschweiler, M. Rethwisch, S. Koppers, J. Stegmaier, "Spherical Harmonics for Shape-Constrained 3D Cell Segmentation", ISBI, 2021.

Data Preparation

The data needs to be in a hdf5 format containing image data for the network input and positional + shape information as output. The data is assumed to be in a structure similar to the following schematic.

-|data_root
----|experiment1
--------|images_as_tif
--------|masks_as_tif
----|experiment2
--------|images_as_tif
--------|masks_as_tif

To prepare your own data, proceed as explained in the following steps:

1. Convert the data using utils.h5_converter.prepare_images and utils.h5_converter.prepare_harmonics to prepare image and mask data, respectively.
2. Create a .csv filelist using utils.csv_generator.create_csv, while the input is assumed to be a list of tuples containing image-mask pairs ->
   [('experiment1/images_converted/im_1.h5', 'experiment1/masks_converted/mask_1.h5'),
...,
('experiment2/images_converted/im_n.h5', 'experiment2/masks_converted/mask_n.h5')]
   

Training and Application

For training and application use the provided scripts and make sure to adjust the data paths in the models.HarmonicNet accordingly.