To get the bounding box of some tissues, say
Large_intestine_lumen
Large_intestine_wall
and test if some points are inside these tissues you can use the GetEntityPointDistance API, e.g., something like this:
import numpy as np
import s4l_v1.model as s4l_model
Vec3 = s4l_model.Vec3
def sample_box(p1: Vec3, p2: Vec3) -> list[Vec3]:
xs = np.linspace(p1[0], p2[0], 10)
ys = np.linspace(p1[1], p2[1], 10)
zs = np.linspace(p1[2], p2[2], 10)
X, Y, Z = np.meshgrid(xs, ys, zs, indexing="ij")
points = np.vstack([X.ravel(), Y.ravel(), Z.ravel()]).T
return [Vec3(p) for p in points]
def find_entities(root_group: s4l_model.EntityGroup, names: list[str]):
entities = s4l_model.CollectEntities([root_group])
entities = [e for e in entities if e.Name in names]
return entities
if __name__ == "__main__":
model_group = s4l_model.AllEntities()["Thelonious_6y_m_v3.1b02_posable"]
entities = find_entities(model_group, ["Large_intestine_lumen", "Large_intestine_wall"])
p1, p2 = s4l_model.GetBoundingBox(entities)
points = sample_box(p1, p2)
inside_gi_tract = np.zeros(len(points), dtype=np.uint8)
for entity in entities:
distance = s4l_model.GetEntityPointDistance(entity, points)
for idx, dist in enumerate(distance):
# note: negative distance means inside the closed surface
if dist.Distance <= 0.0:
inside_gi_tract[idx] = True
