""" Brightfield TFM & Cropped Input ============================================== This example calculates traction forces around an individual immune cell (NK92 natural killer cell) during migrtion in a collagen 1.2mg/ml networks (Batch C). Here simple brightfield image stacks are used to calculate the matrix deformations & forces around the cell. We compare the contracted state with the previous time step 30 seconds earlier. The cell of interest is cropped from a larger field of view. This example can also be evaluated within the graphical user interface. .. figure:: ../images/examples/brightfield_tfm/2d.gif :scale: 100% :align: center """ import saenopy # sphinx_gallery_thumbnail_path = '../../saenopy/img/thumbnails/BFTFM_2.png' # %% # Loading the Stacks # ------------------ # # Saenopy is very flexible in loading stacks from any filename structure. # Here, we use only brightfield images without additional channels. # We compare the stack in the contracted state with a reference state 30 seconds earlier. # We load one multitiff file per stack, where each individual image corresponds to the [z] position. # Experimentally, it can be convenient to take a larger field of view and crop it later to an area of interest. # For this purpose, we use the "crop" parameter, which specifies the boundaries of region of intrest (in pixel). # The "crop" parameter can be set both from the user interface and from the Python code. # # .. figure:: ../images/examples/brightfield_tfm/crop.png # # # We load the relaxed and the contracted stack by using # the placeholder [z] for the z stack in mutlitiffs results = saenopy.get_stacks( 'BrightfieldNK92Data/2023_02_14_12_0920_stack.tif[z]', reference_stack='BrightfieldNK92Data/2023_02_14_12_0850_stack.tif[z]', output_path='BrightfieldNK92Data/example_output', voxel_size=[0.15, 0.15, 2.0], crop={'x': (1590, 2390), 'y': (878, 1678), 'z': (30, 90)}, ) # %% # Detecting the Deformations # -------------------------- # Saenopy uses 3D Particle Image Velocimetry (PIV) with the following parameters # to calculate matrix deformations between a deformed and relaxed state. # # # # +------------------+-------+ # | Piv Parameter | Value | # +==================+=======+ # | element_size | 4.8 | # +------------------+-------+ # | window_size | 12.0 | # +------------------+-------+ # | signal_to_noise | 1.3 | # +------------------+-------+ # | drift_correction | True | # +------------------+-------+ # # Small image features enable to measure 3D deformations from the brightfield stack # # .. figure:: ../images/examples/brightfield_tfm/bf_scroll.gif # :scale: 100% # :align: center # # # define the parameters for the piv deformation detection piv_parameters = {'element_size': 4.8, 'window_size': 12.0, 'signal_to_noise': 1.3, 'drift_correction': True} # iterate over all the results objects for result in results: # set the parameters result.piv_parameters = piv_parameters # get count count = len(result.stacks) if result.stack_reference is None: count -= 1 # iterate over all stack pairs for i in range(count): # or two consecutive stacks if result.stack_reference is None: stack1, stack2 = result.stacks[i], result.stacks[i + 1] # get both stacks, either reference stack and one from the list else: stack1, stack2 = result.stack_reference, result.stacks[i] # and calculate the displacement between them result.mesh_piv[i] = saenopy.get_displacements_from_stacks(stack1, stack2, piv_parameters["window_size"], piv_parameters["element_size"], piv_parameters["signal_to_noise"], piv_parameters["drift_correction"]) # save the displacements result.save() # %% # Generating the Finite Element Mesh # ---------------------------------- # We interpolate the found deformations onto a new mesh which will be used for the regularisation. # with the following parameters. # # +------------------+-------+ # | Mesh Parameter | Value | # +==================+=======+ # | element_size | 4.0 | # +------------------+-------+ # | mesh_size_same | 'piv' | # +------------------+-------+ # | reference_stack | 'next'| # +------------------+-------+ # # define the parameters to generate the solver mesh and interpolate the piv mesh onto it mesh_parameters = {'reference_stack': 'next', 'element_size': 4.0, 'mesh_size': 'piv'} # iterate over all the results objects for result in results: # correct for the reference state displacement_list = saenopy.subtract_reference_state(result.mesh_piv, mesh_parameters["reference_stack"]) # set the parameters result.mesh_parameters = mesh_parameters # iterate over all stack pairs for i in range(len(result.mesh_piv)): # and create the interpolated solver mesh result.solvers[i] = saenopy.interpolate_mesh(result.mesh_piv[i], displacement_list[i], mesh_parameters) # save the meshes result.save() # %% # Calculating the Forces # ---------------------- # Define the material model and run the regularisation to fit the measured deformations and get the forces. # # +--------------------+---------+ # | Material Parameter | Value | # +====================+=========+ # | k | 6062 | # +--------------------+---------+ # | d_0 | 0.0025 | # +--------------------+---------+ # | lambda_s | 0.0804 | # +--------------------+---------+ # | d_s | 0.034 | # +--------------------+---------+ # # +--------------------------+---------+ # | Regularisation Parameter | Value | # +==========================+=========+ # | alpha | 10**11 | # +--------------------------+---------+ # | step_size | 0.33 | # +--------------------------+---------+ # | max_iterations | 300 | # +--------------------------+---------+ # | rel_conv_crit | 0.01 | # +--------------------------+---------+ # # define the parameters to generate the solver mesh and interpolate the piv mesh onto it material_parameters = {'k': 6062.0, 'd_0': 0.0025, 'lambda_s': 0.0804, 'd_s': 0.034} solve_parameters = {'alpha': 10**11, 'step_size': 0.33, 'max_iterations': 300, 'rel_conv_crit': 0.01} # iterate over all the results objects for result in results: result.material_parameters = material_parameters result.solve_parameters = solve_parameters for index, M in enumerate(result.solvers): # set the material model M.set_material_model(saenopy.materials.SemiAffineFiberMaterial( material_parameters["k"], material_parameters["d_0"], material_parameters["lambda_s"], material_parameters["d_s"], )) # find the regularized force solution M.solve_regularized(alpha=solve_parameters["alpha"], step_size=solve_parameters["step_size"], max_iterations=solve_parameters["max_iterations"], rel_conv_crit=solve_parameters["rel_conv_crit"], verbose=True) # save the forces result.save() # clear the cache of the solver results.clear_cache(index) # %% # Display Results # ---------------------- # # .. figure:: ../images/examples/brightfield_tfm/reconstruction.png # # The reconstructed force field (right) generates a reconstructed deformation field (left) # that recapitulates the measured matrix deformation field (upper video). The overall cell contractility is # calculated as all force components pointing to the force epicenter. # # .. figure:: ../images/examples/brightfield_tfm/nans.png # # The cell occupied area is omitted since the signal to noise filter replaces the limited information with Nan values (Grey Dots). # Therefore, no additional segmentation is required. Since we are working with simple brightfield images here, we # do not have information below and above the cell. #