--- a
+++ b/lung_segment.py
@@ -0,0 +1,60 @@
+"""
+This script is to segment the lung out of background as a prepocessing for lobes segementation.
+"""
+import SimpleITK as sitk
+import gui
+
+class LungSegment:
+    """
+    This class is designed for 3D segmentation of lung, including the methods:
+    ...
+    """
+    def __init__(self, img):
+        self.img = img
+        self.temp_img = None
+        self.img_uint8 = None
+
+    def conv_2_uint8(self, WINDOW_LEVEL=(1050,500)):
+        """
+        Convert original image to 8-bit image
+        :param WINDOW_LEVEL: Using an external viewer (ITK-SNAP or 3DSlicer)
+                             we identified a visually appealing window-level setting
+        :return: None
+        """
+        # self.img_uint8 = sitk.Cast(self.img,
+        #                           sitk.sitkUInt8)
+        self.img_uint8 = sitk.Cast(sitk.IntensityWindowing(self.img,
+                                  windowMinimum=WINDOW_LEVEL[1] - WINDOW_LEVEL[0] / 2.0,
+                                  windowMaximum=WINDOW_LEVEL[1] + WINDOW_LEVEL[0] / 2.0),
+                                  sitk.sitkUInt8)
+
+    def regiongrowing(self, seed_pts):
+        """
+        Implement ConfidenceConnected by SimpleITK tools with given seed points
+        :param seed_pts: seed points for region growing [(z,y,x), ...]
+        :return: None
+        """
+        self.temp_img = sitk.ConfidenceConnected(self.img, seedList=seed_pts,
+                                                           numberOfIterations=0,
+                                                           multiplier=2,
+                                                           initialNeighborhoodRadius=1,
+                                                           replaceValue=1)
+
+    def image_showing(self, title=''):
+        """
+        Showing image.
+        :return: None
+        """
+        gui.MultiImageDisplay(image_list=[sitk.LabelOverlay(self.img_uint8, self.temp_img)],
+                              title_list=[title])
+
+    def image_closing(self, size=7):
+        """
+        Implement morphological closing to fix the "holes" inside the image.
+        :param size: the size the closing kernel
+        :return: None
+        """
+        closing = sitk.BinaryMorphologicalClosingImageFilter()
+        closing.SetForegroundValue(1)
+        closing.SetKernelRadius(size)
+        self.temp_img = closing.Execute(self.temp_img)
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