--- a
+++ b/Dicom.py
@@ -0,0 +1,66 @@
+import numpy as np
+import pydicom as dicom
+
+def getSegmentedPixelColor (value, intervals):
+  for i in range(len(intervals)):
+    if value >= intervals[i][0] and value <= intervals[i][1]:
+      return intervals[i][2]
+  return [0,0,0]
+
+# Linear transformation : from [bt < pxvalue < wt] linear to [0 <pyvalue< 255] !important: has loss of information
+def linearTransform(pxvalue, bt, wt):
+    if pxvalue < bt:
+        y=0
+    elif pxvalue > wt:
+        y=255
+    else:
+        y=pxvalue*255/(wt-bt)-255*bt/(wt-bt)
+    return y
+
+# Linear transformation : convert to Hounsfield units (HU)
+def getHuPixels (pixels_array, rows, cols, intercept, slope):
+    m = np.zeros((rows, cols), np.int16)
+    for i in range(rows):
+      for j in range(cols):
+        m[i][j] = pixels_array[i][j] * slope + intercept
+    return m
+
+class Dicom:
+  def __init__(self, src):
+    self.__ds = dicom.dcmread(src)
+    self.__patientId = self.__ds.PatientID
+    self.__cols = self.__ds.Columns
+    self.__rows = self.__ds.Rows
+    self.__huPixelsArray = getHuPixels(self.__ds.pixel_array, self.__rows, self.__cols, self.__ds.RescaleIntercept, self.__ds.RescaleSlope)
+
+  def getPatientId (self):
+    return self.__patientId
+
+  def getPixelsArray (self):
+    return self.__huPixelsArray
+
+  def getRawPixelsArray (self):
+    return self.__ds.pixel_array
+
+  def getLinearRGB (self, bt, wt):
+    image = np.zeros((self.__rows, self.__cols, 3), np.uint8)
+    for i in range(self.__rows):
+      for j in range(self.__cols):
+        color = linearTransform(self.getPixelsArray()[i][j], bt, wt)
+        image[i][j] = (color,color,color)
+    return image
+  
+  # Remember, open-cv uses BGR color system
+  def getSegmentedRGB (self, intervals = [(-3000,-1000,[0,0,0]),(-15,15,[255,0,128]),(20,50,[255,0,0]),(60,100,[0,0,255]),(101,3000,[255,255,255])]): # List of intervals to filter
+    image = np.zeros((self.__rows, self.__cols, 3), np.uint8)
+    for i in range(self.__rows):
+      for j in range(self.__cols):
+          image[i][j] = getSegmentedPixelColor(self.getPixelsArray()[i][j], intervals)
+    return image
+
+  def showHistogram (self):
+    import matplotlib.pyplot as plt
+    plt.hist(self.getPixelsArray().flatten(), bins=50, color='c')
+    plt.xlabel("Hounsfield Units (HU)")
+    plt.ylabel("Frequency")
+    plt.show()