- Various algorithms to correct motion in FLIM (.ptu and .pt3) files
- Full Documentation: https://motion-correction.readthedocs.io.
To install motion_correction, run this command in your terminal:
$ pip install motion_correction
Or for GPU Support (not supported on mac)
$ pip install motion_correction[gpu]This is the preferred method to install motion_correction, as it will always install the most recent stable release.
If you don't have pip installed, this Python installation guide can guide you through the process.
Some algorithms run faster with a GPU. CUDA Toolkit 11.2 - 11.8 must be installed to run on GPU.
Alternatively,
$ conda install -c "nvidia/label/cuda-11.8.0" cuda-toolkit`Refer to this this tutorial notebook for correcting FLIM images in a desktop environment.
To use motion_correction in a script:
from motion_correction import load_ptfile, write_pt3, get_intensity_stack, apply_correction_flim, calculate_correctionLoad a pt3 or ptu file as a numpy array (flim_data_stack):
#The dimensions of flim_data_stack are (width,height,channels,repititions,nanotimes)
flim_data_stack, meta = load_ptfile('input.pt3')Convert flim data stack to an intensity stack for a single channel. Shape: (width,height,repititions):
intensity_stack = get_intensity_stack(flim_data_stack, 2)Choose a local and/or global correction algorithm:
from motion_correction.algorithms import Morphic
morphic = Morphic(radius=16)Correct intensity stack:
results = calculate_correction(intensity_stack, 0, local_algorithm=morphic)Apply correction to flim data:
transform_matrix = results['combined_transforms']
corrected_flim_data_stack = apply_correction_flim(flim_data_stack, transform_matrix)Write to .pt3:
write_pt3(meta, corrected_flim_data_stack, "output.pt3")
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