Added per-patient pixel (voxel) distribution for different regions

utils/miccai.py

@@ -68,8 +68,8 @@ def __init__(self, patient_dir: str):
         self.meta_data = self.get_meta_data()
 
         self._image = Volume(self.meta_data["image"])
-        # self._landmarks = None
         self._structures = self.load_structures()
+        self._landmarks = None
 
     @property
     def image(self) -> Volume:
@@ -83,9 +83,9 @@ def structures(self) -> AttrDict:
     def num_slides(self) -> int:
         return self.image.data.shape[1]
 
-    # @property
-    # def landmarks(self):
-    #     return self._landmarks
+    @property
+    def landmarks(self):
+        return self._landmarks
 
     @property
     def patient_dir(self) -> str:
@@ -102,6 +102,11 @@ def load_structures(self) -> AttrDict:
         return temp
 
     def combine_structures(self, structure_list: list) -> np.ndarray:
+        """
+        This is used as a workaround for overlaying multiple segmentation masks
+        (each corresponding to different region) over a slide. The "correct" way
+        can be quite complicated, and is not worth the time for now.
+        """
         assert len(structure_list) > 1, "A minimum of 2 structures are required"
         structure_arrays = []
 

utils/visualize.py

@@ -1,5 +1,6 @@
 import ipywidgets as widgets
 import matplotlib.pyplot as plt
+import seaborn as sns
 from ipywidgets import fixed, interact
 
 from .miccai import STRUCTURES, Patient
@@ -33,6 +34,30 @@ def plot_slide(patient: Patient, index=0, region=None):
     return axes
 
 
+def plot_region_distribution(patient: Patient, exclude=None, ax=None):
+    voxel_dict = {}
+    if exclude is None:
+        exclude = []
+    elif isinstance(exclude, str):
+        exclude = [exclude]
+
+    for structure in STRUCTURES:
+        if structure not in exclude:
+            region_volume = patient.structures[structure]
+            if region_volume is not None:
+                voxel_dict[structure] = patient.image.as_numpy()[
+                    region_volume.as_numpy() == 1
+                ]
+
+    ax = sns.boxplot(
+        data=list(voxel_dict.values()), showmeans=True, showfliers=False, ax=ax
+    )
+    ax.set_xticklabels(voxel_dict.keys(), rotation=45)
+    ax.set_ylabel("Hounsfield Units (HU)")
+
+    return ax
+
+
 def notebook_interact(patient: Patient):
     return interact(
         plot_slide,