Skip to content

Commit 1e2533f

Browse files
Update documentation and readme
1 parent d883a07 commit 1e2533f

File tree

3 files changed

+18
-19
lines changed

3 files changed

+18
-19
lines changed

README.md

Lines changed: 7 additions & 18 deletions
Original file line numberDiff line numberDiff line change
@@ -1,21 +1,10 @@
1-
# Synaptic Reconstruction
1+
# SynapseNet: Deep Learning for Automatic Synapse Reconstruction
22

3-
Reconstruction of synaptic structures in electron microscopy.
3+
SynapseNet is a tool for segmentation and analysis of synapses in electron microscopy.
44

5-
THIS IS WORK IN PROGRESS!
5+
To learn how to use SynapseNet, check out [the documentation](https://computational-cell-analytics.github.io/synapse-net/).
6+
To learn more about how it works, check out [our preprint](TODO).
67

7-
## Installation
8-
9-
- Make sure conda or mamba is installed.
10-
- If you don't have a conda installation yet we recommend [micromamba](https://mamba.readthedocs.io/en/latest/installation/micromamba-installation.html)
11-
- Create the environment with all required dependencies: `mamba env create -f environment.yaml`
12-
- Activate the environment: `mamba activate synaptic-reconstruction`
13-
- Install the package: `pip install -e .`
14-
15-
## Tools
16-
17-
### Segmentation Correction
18-
19-
https://napari.org/stable/howtos/layers/labels.html
20-
21-
### Distance Measurements
8+
See an example reconstruction of a mossy fibre synapse with SynapseNet.
9+
Automatic segmentation of synaptic vesicles are rendered in orange, active zones in blue and two mitochondria in red and cyan.
10+
![Reconstruction of a mossy fiber synapse](doc/images/synapse-reconstruction.png)

doc/images/synapse-reconstruction.png

902 KB
Loading

doc/start_page.md

Lines changed: 11 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -14,15 +14,25 @@ especially throught the [domain adaptation](domain-adaptation) functionality.
1414
SynapseNet offers a [napari plugin](napari-plugin), [command line interface](command-line-interface), and [python library](python-library).
1515
Please cite our [bioRxiv preprint](TODO) if you use it in your research.
1616

17-
## Installation
17+
**The rest of the documentation will be updated in the next days!**
18+
19+
## Requirements & Installation
1820

1921
- Requirements: Tested on Linux but should work on Mac/Windows.
2022
- GPU needed to use 3d segmentation networks
2123
- Installation via conda and local pip install
2224
- GPU support
2325

26+
- Make sure conda or mamba is installed.
27+
- If you don't have a conda installation yet we recommend [micromamba](https://mamba.readthedocs.io/en/latest/installation/micromamba-installation.html)
28+
- Create the environment with all required dependencies: `mamba env create -f environment.yaml`
29+
- Activate the environment: `mamba activate synaptic-reconstruction`
30+
- Install the package: `pip install -e .`
31+
2432
## Napari Plugin
2533

34+
lorem ipsum
35+
2636
## Command Line Functionality
2737

2838
- segmentation cli

0 commit comments

Comments
 (0)