FIX: Correctly handle Philips DICOMs w/ derived volume

.gitmodules

@@ -16,3 +16,6 @@
 [submodule "nibabel-data/nitest-cifti2"]
 	path = nibabel-data/nitest-cifti2
 	url = https://github.com/demianw/nibabel-nitest-cifti2.git
+[submodule "nibabel-data/nitest-dicom"]
+	path = nibabel-data/nitest-dicom
+	url = https://github.com/effigies/nitest-dicom

nibabel/nicom/dicomwrappers.py

@@ -14,14 +14,15 @@
 from __future__ import division
 
 import operator
+import warnings
 
 import numpy as np
 
 from . import csareader as csar
 from .dwiparams import B2q, nearest_pos_semi_def, q2bg
 from ..openers import ImageOpener
 from ..onetime import setattr_on_read as one_time
-from ..pydicom_compat import tag_for_keyword
+from ..pydicom_compat import tag_for_keyword, Sequence
 
 
 class WrapperError(Exception):
@@ -502,8 +503,32 @@ def image_shape(self):
         rows, cols = self.get('Rows'), self.get('Columns')
         if None in (rows, cols):
             raise WrapperError("Rows and/or Columns are empty.")
+
         # Check number of frames
+        first_frame = self.frames[0]
         n_frames = self.get('NumberOfFrames')
+        # some Philips may have derived images appended
+        has_derived = False
+        if hasattr(first_frame, 'get') and first_frame.get([0x18, 0x9117]):
+            # DWI image may include derived isotropic, ADC or trace volume
+            try:
+                self.frames = Sequence(
+                    frame for frame in self.frames if
+                    frame.MRDiffusionSequence[0].DiffusionDirectionality
+                    != 'ISOTROPIC'
+                    )
+            except IndexError:
+                # Sequence tag is found but missing items!
+                raise WrapperError("Diffusion file missing information")
+            except AttributeError:
+                # DiffusionDirectionality tag is not required
+                pass
+            else:
+                if n_frames != len(self.frames):
+                    warnings.warn("Derived images found and removed")
+                    n_frames = len(self.frames)
+                    has_derived = True
+
         assert len(self.frames) == n_frames
         frame_indices = np.array(
             [frame.FrameContentSequence[0].DimensionIndexValues
@@ -522,6 +547,15 @@ def image_shape(self):
         if stackid_tag in dim_seq:
             stackid_dim_idx = dim_seq.index(stackid_tag)
             frame_indices = np.delete(frame_indices, stackid_dim_idx, axis=1)
+            dim_seq.pop(stackid_dim_idx)
+        if has_derived:
+            # derived volume is included
+            derived_tag = tag_for_keyword("DiffusionBValue")
+            if derived_tag not in dim_seq:
+                raise WrapperError("Missing information, cannot remove indices "
+                                   "with confidence.")
+            derived_dim_idx = dim_seq.index(derived_tag)
+            frame_indices = np.delete(frame_indices, derived_dim_idx, axis=1)
         # account for the 2 additional dimensions (row and column) not included
         # in the indices
         n_dim = frame_indices.shape[1] + 2

nibabel/nicom/tests/test_dicomwrappers.py

@@ -21,6 +21,7 @@
                         assert_not_equal, assert_raises)
 
 from numpy.testing import assert_array_equal, assert_array_almost_equal
+from ...tests.nibabel_data import get_nibabel_data, needs_nibabel_data
 
 IO_DATA_PATH = pjoin(dirname(__file__), 'data')
 DATA_FILE = pjoin(IO_DATA_PATH, 'siemens_dwi_1000.dcm.gz')
@@ -36,6 +37,8 @@
 DATA_FILE_DEC_RSCL = pjoin(IO_DATA_PATH, 'decimal_rescale.dcm')
 DATA_FILE_4D = pjoin(IO_DATA_PATH, '4d_multiframe_test.dcm')
 DATA_FILE_EMPTY_ST = pjoin(IO_DATA_PATH, 'slicethickness_empty_string.dcm')
+DATA_FILE_4D_DERIVED = pjoin(get_nibabel_data(), 'nitest-dicom',
+                             '4d_multiframe_with_derived.dcm')
 
 # This affine from our converted image was shown to match our image spatially
 # with an image from SPM DICOM conversion. We checked the matching with SPM
@@ -622,6 +625,14 @@ def test_slicethickness_fallback(self):
         dw = didw.wrapper_from_file(DATA_FILE_EMPTY_ST)
         assert_equal(dw.voxel_sizes[2], 1.0)
 
+    @dicom_test
+    @needs_nibabel_data('nitest-dicom')
+    def test_data_derived_shape(self):
+        # Test 4D diffusion data with an additional trace volume included
+        # Excludes the trace volume and generates the correct shape
+        dw = didw.wrapper_from_file(DATA_FILE_4D_DERIVED)
+        assert_equal(dw.image_shape, (96, 96, 60, 33))
+
     @dicom_test
     def test_data_fake(self):
         # Test algorithm for get_data

nibabel/pydicom_compat.py

@@ -21,22 +21,24 @@
 import numpy as np
 
 have_dicom = True
-pydicom = read_file = tag_for_keyword = None
+pydicom = read_file = tag_for_keyword = Sequence = None
 
 try:
     import dicom as pydicom
-    # Values not imported by default
-    import dicom.values
 except ImportError:
     try:
         import pydicom
     except ImportError:
         have_dicom = False
     else:  # pydicom module available
         from pydicom.dicomio import read_file
+        from pydicom.sequence import Sequence
         # Values not imported by default
         import pydicom.values
 else:  # dicom module available
+    # Values not imported by default
+    import dicom.values
+    from dicom.sequence import Sequence
     read_file = pydicom.read_file
 
 if have_dicom: