GUI#

PyNutil also includes a desktop GUI for running the main workflow without writing Python code.

Installation#

Download the Windows or macOS executable from the PyNutil releases page.

If you prefer to install the GUI from source in a Python environment, install PyNutil with the gui extra from the repository root:

pip install -e .[gui]

Then launch the GUI with:

python gui/PyNutilGUI.py

PyNutil GUI screenshot

What the GUI does#

The GUI wraps the same core pipeline as the Python API:

  • load a BrainGlobe atlas or a custom atlas

  • read a registration JSON

  • process either segmentation images or intensity images

  • quantify the result by atlas region

  • optionally build interpolated 3D volumes

  • save reports and MeshView / NIfTI outputs

Required inputs#

The GUI expects:

  1. A registration JSON

  2. Either a segmentation folder or an image folder

  3. An output folder

  4. An atlas selection

For segmentation workflows you also choose the object color to quantify.

Atlas choices#

You can run the GUI with either:

  • a BrainGlobe atlas selected by name

  • a custom atlas defined by annotation and label files

BrainGlobe atlases can also be installed from the GUI workflow.

Segmentation and intensity modes#

The GUI supports two main analysis modes:

Segmentation mode#

Use this when your input folder contains segmentation images and you want to count segmented structures by atlas region.

Typical inputs:

  • registration JSON

  • segmentation folder

  • object color

  • atlas

Typical outputs:

  • whole_series_report/counts.csv

  • MeshView point clouds

  • optional interpolated volumes

Intensity mode#

Use this when your input folder contains source images and you want to measure signal intensity by atlas region instead of counting segmented objects.

Typical inputs:

  • registration JSON

  • image folder

  • atlas

Typical outputs:

  • whole_series_report/intensity.csv

  • MeshView exports using intensity values

  • optional interpolated volumes

Optional volume interpolation#

The GUI can generate 3D volumes from the section data. When interpolation is enabled, you can choose the value mode:

  • pixel_count

  • mean

  • object_count

These outputs can be written as NIfTI files for downstream viewing.

Output folders#

The GUI writes the same output structure as the Python API. Common outputs include:

  • whole_series_report/

  • whole_series_meshview/

  • interpolated_volume/

Depending on the workflow, these may include:

Output

Description

counts.csv

Region-level segmentation quantification

intensity.csv

Region-level intensity quantification

pixels_meshview.json

Atlas-space point cloud export

objects_meshview.json

Object-centroid point cloud export

interpolated_volume.nii.gz

Interpolated value volume

frequency_volume.nii.gz

Per-voxel sampling frequency

damage_volume.nii.gz

Binary damage mask volume