Metadata-Version: 2.4
Name: exhale-lung
Version: 1.3.1
Summary: EXHALE, Efficient X-ray Hub Aiding Lung Explorations
Author: Tom Delaire, Emanuel Larsson, Bryan Falcones, Karina Thånell
Author-email: Carl Troein <carl.troein@cec.lu.se>
License-Expression: MIT
Project-URL: Homepage, https://github.com/ctroein/exhale
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: scikit-learn
Requires-Dist: pandas
Requires-Dist: h5py
Requires-Dist: napari
Requires-Dist: imageio
Requires-Dist: silx
Requires-Dist: csbdeep
Requires-Dist: pyqt5
Requires-Dist: tensorflow==2.15.*; sys_platform == "win32"
Requires-Dist: tensorflow; sys_platform != "win32"
Requires-Dist: stardist
Dynamic: license-file

# EXHALE
## Efficient X-ray Hub Aiding Lung Explorations

This project aims to develop a specialized tool for investigating elemental aspects of chronic lung diseases. 

From the [VINNOVA project
description](https://www.vinnova.se/en/p/exhale--efficient-x-ray-hub-aiding-lung-explorations/):  
The purpose of this project is to advance understanding and treatment of
chronic lung diseases, leading causes of mortality worldwide, by
characterizing elements in lung tissue suspected to impact their
pathogenesis. The industrial partners TrulyLabs and AnaMar in collaboration
with MAX IV, Lung Biology and Correlative Image Processing and Analysis
(CIPA) fom Lund University, aim to streamline a workflow of X-ray imaging
studies for lung diseases, making these methods more accessible for
biomedical companies and clinical researchers.

## Currect functionality

* Loading HDF5 files with XRF data from the NanoMAX beamline at MAX IV.
* Composing element maps into publication-ready figures.
* Segmentation of cells and clustering of areas in element maps.
