.

helpers/images.py

@@ -6,7 +6,11 @@ from io import BytesIO
 from PIL import Image, ImageFile
 
 import pydicom
-from .pydicom_PIL import get_PIL_image
+
+try:
+    from .pydicom_PIL import get_PIL_image
+except:
+    from pydicom_PIL import get_PIL_image
 
 def image_as_base64(image_file):
     """
@@ -42,11 +46,11 @@ def pil_dicom_image(source, exif_orientation=True, **options):
     #    return
     #source = BytesIO(source.read())
 
-    print("start pdi")
+    # open file with pydicom
-
     ds = pydicom.read_file(source)
 
-    image = get_PIL_image(ds)
+    # return the image file
+    return get_PIL_image(ds)
 
     #with Image.open(source) as image:
     #    # Fully load the image now to catch any problems with the image contents.
@@ -58,4 +62,10 @@ def pil_dicom_image(source, exif_orientation=True, **options):
 
     #if exif_orientation:
     #    image = utils.exif_orientation(image)
-    return image
+
+
+
+def show_PIL(dataset):
+    """Display an image using the Python Imaging Library (PIL)"""
+    im = get_PIL_image(dataset)
+    im.show()

helpers/pydicom_PIL.py

@@ -23,7 +23,10 @@ and Python Imaging Library:
 
 have_PIL = True
 try:
-    import PIL.Image
+    import PIL.Image, PIL.ImageOps
+
+    from pydicom.pixel_data_handlers.util import apply_voi_lut, apply_modality_lut
+
 except ImportError:
     have_PIL = False
 
@@ -59,6 +62,13 @@ def get_PIL_image(dataset):
     if ('PixelData' not in dataset):
         raise TypeError("Cannot show image -- DICOM dataset does not have "
                         "pixel data")
+
+
+    # Apply modality lut
+    array = apply_modality_lut(dataset.pixel_array, dataset)
+    # voi lut doesn't seem to help
+    #array = apply_voi_lut(array, dataset)
+
     # can only apply LUT if these window info exists
     if ('WindowWidth' not in dataset) or ('WindowCenter' not in dataset):
         bits = dataset.BitsAllocated
@@ -79,19 +89,28 @@ def get_PIL_image(dataset):
         # PIL size = (width, height)
         size = (dataset.Columns, dataset.Rows)
 
+        array = apply_modality_lut(dataset.pixel_array, dataset)
+
+        array = apply_voi_lut(array, dataset)
+
+        if dataset["PhotometricInterpretation"].value == "MONOCHROME1":
+            # We need to invert
+            array = np.invert(array)
+
+        pixel_data = array.tostring()
         # Recommended to specify all details
         # by http://www.pythonware.com/library/pil/handbook/image.htm
-        im = PIL.Image.frombuffer(mode, size, dataset.PixelData,
+        im = PIL.Image.frombuffer(mode, size, pixel_data,
                                   "raw", mode, 0, 1)
-
     else:
         ew = dataset['WindowWidth']
         ec = dataset['WindowCenter']
         ww = int(ew.value[0] if ew.VM > 1 else ew.value)
         wc = int(ec.value[0] if ec.VM > 1 else ec.value)
-        image = get_LUT_value(dataset.pixel_array, ww, wc)
+
-        # Convert mode to L since LUT has only 256 values:
+        ## Convert mode to L since LUT has only 256 values:
-        #   http://www.pythonware.com/library/pil/handbook/image.htm
+        ##   http://www.pythonware.com/library/pil/handbook/image.htm
+        image = get_LUT_value(array, ww, wc)
         im = PIL.Image.fromarray(image).convert('L')
 
     return im