--- a
+++ b/functions.py
@@ -0,0 +1,103 @@
+import cv2
+import numpy as np
+import os
+import dicom
+from pylab import *
+from mpl_toolkits.mplot3d import Axes3D
+slices=[]
+def dicomRead(path):
+
+    for dirName, subdirList, fileList in os.walk(path):
+        for filename in fileList:
+            if ".dcm" in filename.lower():
+                slices.append(dicom.read_file(os.path.join(dirName, filename)))
+    slices.sort(key=lambda x: int(x.ImagePositionPatient[2]))
+    try:
+        slice_thickness = np.abs(slices[0].ImagePositionPatient[2] - slices[1].ImagePositionPatient[2])
+    except:
+        slice_thickness = np.abs(slices[0].SliceLocation - slices[1].SliceLocation)
+
+    for s in slices:
+        s.SliceThickness = slice_thickness
+    image = np.stack([s.pixel_array for s in slices])
+    return image[0:255,:,:]
+def floodfill(image, start_point, value):
+    height, width = image.shape[:2]
+    points = [start_point]
+    flag = [[0 for j in range(width)] for i in range(height)]
+    flag[start_point[0]][start_point[1]] = 1
+    origin_value = image[start_point[0]][start_point[1]]
+    while len(points) > 0:
+        pt = points.pop(0)
+        dx = [0, 1, 0, -1]
+        dy = [1, 0, -1, 0]
+        for x, y in zip(dx, dy):
+            if (0 <= pt[0] + x < height and 0 <= pt[1] + y < width and
+                        origin_value == image[pt[0] + x][pt[1] + y] and
+                        flag[pt[0] + x][pt[1] + y] == 0):
+                flag[pt[0] + x][pt[1] + y] = 1
+                points.append((pt[0] + x, pt[1] + y))
+        image[pt[0]][pt[1]] = value
+    return image
+
+
+def switch_pixels(image, origin_value, value):
+    for i in range(image.shape[0]):
+        for j in range(image.shape[1]):
+            if image[i][j] == origin_value:
+                image[i][j] = value
+    return image
+
+def morphology_open(image):
+    # morphology open operation
+    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5))
+    image = cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel)
+    return image
+
+def segment(image):
+    threashold=625
+    mask = np.copy(image)
+
+    mask = morphology_open(mask)
+    ret, mask = cv2.threshold(mask, threashold, 255, cv2.THRESH_BINARY_INV)
+
+    # set margin to black
+    h, w = mask.shape[:2]
+    for i in range(h):
+        for j in range(w):
+            if ((i == 0 or j == 0 or i == h - 1 or j == w - 1) and
+                        mask[i][j] != 0):
+                mask = floodfill(mask, (i, j), 0)
+
+    # fill holes in middle
+    mask = floodfill(mask, (0, 0), -1)
+    mask = switch_pixels(mask, 0, 255)
+    mask = switch_pixels(mask, -1, 0)
+    return mask
+
+
+def test3D(ConstPixelDims = None):
+    xx, yy = np.meshgrid(np.linspace(0, 1, 512), np.linspace(0, 1, 512))
+    X = xx
+    Y = yy
+    #Z = i
+    ax2 = gca(projection='3d')
+    off = 4000 / (ConstPixelDims[2] - 1)
+    for i in range(ConstPixelDims[2]):  # ConstPixelDims[2]
+        tempImage = ArrayDicom[:, :, i]
+        tempImage = np.ma.masked_where(tempImage < 1200, tempImage)
+        print("i : " + str(i))
+        print("tempImage.shape[0] " + str(tempImage.shape[0]))
+        print("tempImage.shape[1] " + str(tempImage.shape[1]))
+        x, y = ogrid[0:tempImage.shape[0], 0:tempImage.shape[1]]
+        ##print("x : " + str(x) + " :: y : " + str(y))
+        Z = 10 * np.ones(X.shape)
+        ax = gca(projection='3d')
+
+        # ax.plot_surface(x, y, Z, rstride=5, cstride=5, facecolors=tempImage,cmap='gray' )
+
+        ax2.contourf(X, Y, tempImage, zdir='z', offset=i * off, antialiased=True)
+
+        # ax2.set_zlim((0.,1.))
+
+    show()
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