Alternative method to segment

pydbt/functions/dataPreProcess.py

@@ -8,6 +8,7 @@
 
 import numpy as np
 from scipy.ndimage.filters import uniform_filter1d
+from skimage.filters import threshold_otsu
 
 def dataPreProcess(proj, geo, flagtransfIntensity=True, flagCropProj=True):
 
@@ -38,7 +39,25 @@ def cropProj(proj):
     secondDv = np.gradient(uniform_filter1d(firstDv, size=100))
 
     # Takes its min second derivative
-    indX = np.argmin(secondDv) - Gap 
+    indX = np.argmin(secondDv)  
+
+    # Alternative method to compare
+    # Otsu
+    thresh = threshold_otsu(proj[:,:,proj.shape[2]//2 - 1])
+
+    # Get mask
+    mask = proj[:,:,proj.shape[2]//2 - 1] < thresh
+
+    # Weight bounds
+    mask_w = np.sum(mask, 0) > 0
+    res = np.where(mask_w == True)
+    w_min, w_max = res[0][0], res[0][-1]
+
+    # If the difference is big, take the min (most left)
+    if np.abs(indX - w_min) > 200:
+        indX = np.min([indX, w_min])
+
+    indX -= Gap
 
     proj_crop = proj[:,indX::,:]