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Modifying Image recon to accept different tissue properties for each wavelength #92

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Modifying Image recon to accept different tissue properties for each wavelength #92

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6 changes: 4 additions & 2 deletions src/cedalion/imagereco/forward_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -627,6 +627,7 @@ def __init__(
assert head_model.crs == geo3d.points.crs

self.head_model = head_model
self.measurement_list = measurement_list

self.optode_pos = geo3d[
geo3d.type.isin([cdc.PointType.SOURCE, cdc.PointType.DETECTOR])
Expand All @@ -645,9 +646,10 @@ def __init__(

self.optode_pos = self.optode_pos.pint.dequantify()
self.optode_dir = self.optode_dir.pint.dequantify()

self.tissue_properties = get_tissue_properties(
self.head_model.segmentation_masks
self.head_model.segmentation_masks,
self.measurement_list.wavelength.unique()
)

self.volume = self.head_model.segmentation_masks.sum("segmentation_type")
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39 changes: 20 additions & 19 deletions src/cedalion/imagereco/tissue_properties.py
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Original file line number Diff line number Diff line change
Expand Up @@ -82,26 +82,27 @@ class TissueType(Enum):
# FIXME allow for wavelength dependencies


def get_tissue_properties(segmentation_masks: xr.DataArray) -> np.ndarray:
def get_tissue_properties(segmentation_masks: xr.DataArray, wavelengths: list) -> np.ndarray:
"""Return tissue properties for the given segmentation mask."""
ntissues = segmentation_masks.sizes["segmentation_type"] + 1
tissue_props = np.zeros((ntissues, 4))
tissue_props[0, :] = [0.0, 0.0, 1.0, 1.0] # background

for st in segmentation_masks.segmentation_type.values:
m = segmentation_masks.sel(segmentation_type=st).values
int_labels = np.unique(m[m > 0])
if len(int_labels) == 0:
warn("Segmentation type %s is empty." % st)
continue
int_label = int_labels.item()

if (tissue_type := TISSUE_LABELS.get(st, None)) is None:
raise ValueError(f"unknown tissue type '{st}'")

tissue_props[int_label, 0] = TISSUE_PROPS_ABSORPTION[tissue_type]
tissue_props[int_label, 1] = TISSUE_PROPS_SCATTERING[tissue_type]
tissue_props[int_label, 2] = TISSUE_PROPS_ANISOTROPY[tissue_type]
tissue_props[int_label, 3] = TISSUE_PROPS_REFRACTION[tissue_type]
n_wavelength = len(wavelengths)
tissue_props = np.zeros((ntissues, 4, n_wavelength)) #FIXME add dimension for multiple wavelengths
for i_wl in range(n_wavelength):
tissue_props[0, :,i_wl] = [0.0, 0.0, 1.0, 1.0] # background

for st in segmentation_masks.segmentation_type.values:
m = segmentation_masks.sel(segmentation_type=st).values
int_label = np.unique(m[m > 0]).item()

if (tissue_type := TISSUE_LABELS.get(st, None)) is None:
raise ValueError(f"unknown tissue type '{st}'")

#FIXME made it so the same properties were assigned to each wavelength
tissue_props[int_label, 0, i_wl] = TISSUE_PROPS_ABSORPTION[tissue_type]
tissue_props[int_label, 1, i_wl] = TISSUE_PROPS_SCATTERING[tissue_type]
tissue_props[int_label, 2, i_wl] = TISSUE_PROPS_ANISOTROPY[tissue_type]
tissue_props[int_label, 3, i_wl] = TISSUE_PROPS_REFRACTION[tissue_type]

return tissue_props

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