add keep objects filter

Filters.py

@@ -17,6 +17,7 @@
 import SimpleITK 
 
 from Segmentation import A_Filter, FILTER_TYPE, UTILITIES_DIR, External_Filter, Simple_ITK_Filter,  Fiji_Filter
+from UsefullFunctions import AttrDict
 
 
 class Apply_Median(External_Filter):
@@ -261,6 +262,70 @@ def set_Filter_ITK(self):
         self.simple_itk_filter.SetKernelType(self.kernel)
     def set_params(self):
         self.params = [self.backgorund, self.foregorund, self.boundary_foreground]
+
+class Keep_N_Objects(A_Filter):
+    """
+    Input should be a label image
+    order 0 for descending order
+    works fine up to 2^16 labels
+    """
+    SIZE = 'Physical Size'
+    FERET_DIAMETER = 'Feret Diameter'
+    PERIMETER = 'Perimeter'
+    ELONGATION = 'Elongation'
+    SPHERICAL_DIAMETER = 'Spherical Diameter' 
+    SPHERICAL_RADIUS = 'Spherical Radius'
+    FLATNESS = 'Flatness'
+    PIXELS = 'Number of Pixels'
+    PIXELS_ON_BORDER = 'Number of pixels on border'
+    PERIMETER_ON_BORDER = 'Perimeter on border'
+    PERIMETER_ON_BORDER_RATIO = 'Perimeter on border ratio'
+    ROUNDNESS = 'Roundness'
+
+
+    def __init__(self, n_objects = 3, feature = SIZE, order = 0, bck_val = 0, save_img =(None,True) ):
+        A_Filter.__init__(self, 'Keep-Objects', FILTER_TYPE.OTHERS, built_in=True, save_img=save_img)
+        self.n_objects = n_objects
+        self.feature = feature
+        self.order = order
+        self.bck_val = bck_val
+
+    def execute(self,inputimage, output = None):
+        self.to_interface(inputimage)
+        shape_stats = SimpleITK.LabelShapeStatisticsImageFilter()
+        FEATS = {Keep_N_Objects.SIZE:shape_stats.GetPhysicalSize,
+                 Keep_N_Objects.ELONGATION:shape_stats.GetElongation,
+                 Keep_N_Objects.SPHERICAL_DIAMETER:shape_stats.GetEquivalentSphericalPerimeter,
+                 Keep_N_Objects.SPHERICAL_RADIUS:shape_stats.GetEquivalentSphericalRadius,
+                 Keep_N_Objects.FERET_DIAMETER:shape_stats.GetFeretDiameter,
+                 Keep_N_Objects.FLATNESS:shape_stats.GetFlatness, 
+                 Keep_N_Objects.PIXELS:shape_stats.GetNumberOfPixels, 
+                 Keep_N_Objects.PIXELS_ON_BORDER:shape_stats.GetNumberOfPixelsOnBorder,
+                 Keep_N_Objects.PERIMETER:shape_stats.GetPerimeter, 
+                 Keep_N_Objects.PERIMETER_ON_BORDER:shape_stats.GetPerimeterOnBorder,
+                 Keep_N_Objects.PERIMETER_ON_BORDER_RATIO:shape_stats.GetPerimeterOnBorderRatio,
+                 Keep_N_Objects.ROUNDNESS:shape_stats.GetRoundness}
+        shape_stats.Execute(self.input_path_and_image.image, self.bck_val,
+                            self.feature == Keep_N_Objects.FERET_DIAMETER, self.feature == Keep_N_Objects.PERIMETER)
+        measures = np.array([FEATS[self.feature](l) for l in shape_stats.GetLabels() ])
+        sorted_selec_labels =  np.array(shape_stats.GetLabels())[measures.argsort()[:self.n_objects]] if self.order != 0 else np.array(shape_stats.GetLabels())[measures.argsort()[-self.n_objects:]]
+
+        type_im = SimpleITK.sitkUInt8 if np.max(sorted_selec_labels)/256 < 1 else SimpleITK.sitkUInt16
+        print type_im
+        self.output_path_and_image.image = SimpleITK.Image(self.input_path_and_image.image.GetSize(),type_im)
+        self.output_path_and_image.image.CopyInformation(self.input_path_and_image.image)
+        print sorted_selec_labels
+        for l in sorted_selec_labels:
+            print l
+            masked = self.input_path_and_image.image == l if type_im == SimpleITK.sitkUInt8 else SimpleITK.Cast(self.input_path_and_image.image == l, SimpleITK.sitkUInt16)
+            self.output_path_and_image.image += masked*l
+
+        self.output_path_and_image.path = self.output_path_and_image.path if output is None else output
+        SimpleITK.WriteImage(self.output_path_and_image.image,self.output_path_and_image.path)
+
+        return self
+
+
 
 
 class Hu_Threshold(A_Filter):

SRM.ijm

@@ -2,8 +2,14 @@
 #@int q
 #@String averages
 #@String threeD
-run("Image Sequence...", "open="+image_path+" sort");
+#@String image_out_path
+print (File.isDirectory(image_path));
+if (File.isDirectory(image_path) == "1") {
+  run("Image Sequence...", "open="+image_path+" sort");
+} else {
+  open(image_path);
+}
 run("8-bit");
 run("Statistical Region Merging", "q="+q+" "+averages+" "+threeD);
-saveAs("Tiff", "/tmp/outSRM.tif");
+run("Save", "save="+image_out_path);
 exit ("No argument!");

Segmentation.py

@@ -145,12 +145,13 @@ class Fiji_Filter(A_Filter):
     def execute(self, a_filter, output = None): #Input and Output can be just paths
         """
         a_filter and image or another filter
+        This version will close all Fiji instances
         """
         self.input_path_and_image.path = a_filter.output_path_and_image.path if isinstance(a_filter,A_Filter) else a_filter
         self.output_path_and_image.path = self.output_path_and_image.path if output is None else output
         self.set_params()
         self.check_params()
-        calling_external('pkill',[ '-f', 'ImageJ*'])
+        calling_external('pkill',[ '-f', 'ImageJ-lin*'])
         calling_external(self.path, ['--ij2', '--headless', '--run', ]+self.params)
         return self
 

UsefullFunctions.py

@@ -145,6 +145,11 @@ def hdr_to_mhd(pathimages):
         pathfinal=os.path.join(os.path.abspath(os.path.join(i, os.pardir)),os.path.basename(os.path.normpath(i)).split('.')[0]+'.mhd')
         SimpleITK.WriteImage(image,pathfinal)
 
+class AttrDict(dict):
+    def __init__(self, *args, **kwargs):
+        super(AttrDict, self).__init__(*args, **kwargs)
+        self.__dict__ = self
+
 
 if __name__ == "__main__":
     print 'Functions'

utilities.py

@@ -12,10 +12,14 @@
 import time
 import os
 
+import glob
+
 from Filters import SRM
 
 
 
+
+
 def itkImageToSLIC(itk_image, n_seg = 1000, compactness = 0.0001, return_itk_image = True):
     """
     Save space
@@ -52,22 +56,43 @@ def srm(itk_image, q = 25, three_dim = True, averages = False ):
     temp_image_path_input = os.path.join(tempfile.gettempdir(),str(time.time())+'.mhd')
     SimpleITK.WriteImage(itk_image, temp_image_path_input)
     temp_image_path_output = os.path.join(tempfile.gettempdir(),str(time.time())+'.mhd')
-    srm = SRM(save_img=(temp_image_path_output, False),q=25)
+    srm = SRM(save_img=(temp_image_path_output, False),q=q)
     srm.execute(temp_image_path_input)
     srm_itk_image = SimpleITK.ReadImage(temp_image_path_output)
     srm_itk_image.CopyInformation(itk_image)
     return srm_itk_image
+
+def test_label_bck():
+    folders = glob.glob('/media/pmacias/DATA2/amunoz/NUS_DATA_2016/PLTB7*/*/')
+    for i, folder in enumerate(folders):
+        images = glob.glob(folder+'/*/*UMAP*')
+        print i, images
+        for image in images:
+            t1s = glob.glob(os.path.split(image)[0]+'/*t1*')
+            for t1 in t1s:
+                print t1
+                t1_im = read_dicom(t1)
+                study = image.split('/')[-2]
+                image_im = read_dicom(image)
+                mask = image_im==0
+                SimpleITK.WriteImage(mask, os.path.join('/tmp/'+study+'.mhd'))
+                SimpleITK.WriteImage(t1_im, os.path.join('/tmp/t1'+study+'.mhd'))
+                SimpleITK.WriteImage(resamplig(t1_im, mask, interpolator=SimpleITK.sitkNearestNeighbor),  os.path.join('/tmp/resam'+study+'.mhd')) 
+
 
 
 
 if __name__ == "__main__":
-    t1_fat_sup_dcm = '/media/pmacias/DATA2/amunoz/NUS_DATA_2016/PLTB706/20131121/102152_812000/t1_vibe_tra_bh_fatsat_exsp_0037'
-    t1_fat_sup = read_dicom(t1_fat_sup_dcm)
+#    t1_fat_sup_dcm = '/media/pmacias/DATA2/amunoz/NUS_DATA_2016/PLTB706/20131121/102152_812000/t1_vibe_tra_bh_fatsat_exsp_0037'
+#    t1_fat_sup = read_dicom(t1_fat_sup_dcm)
 #    t1_fat_sup_slic = itkImageToSLIC(t1_fat_sup)
 #    SimpleITK.WriteImage(t1_fat_sup_slic, '/tmp/slic_res.mhd')
-    t1_seg = srm(t1_fat_sup)
-    pt_dcm = '/media/pmacias/DATA2/amunoz/NUS_DATA_2016/PLTB706/20131121/102152_812000/_Tho_MRAC_PET_15_min_list_AC_Images_0020/'
-    pt = read_dicom(pt_dcm)
-    SimpleITK.WriteImage(resamplig(pt,t1_seg), 'labels_to_pet.mhd')
+#    t1_seg = srm(t1_fat_sup, q=2)
+#    pt_dcm = '/media/pmacias/DATA2/amunoz/NUS_DATA_2016/PLTB706/20131121/102152_812000/_Tho_MRAC_PET_15_min_list_AC_Images_0020/'
+#    pt = read_dicom(pt_dcm)
+#    SimpleITK.WriteImage(resamplig(pt,t1_seg, interpolator=SimpleITK.sitkNearestNeighbor), '/tmp/labels_to_pet_NN.mhd')
+#    pt = SimpleITK.Cast(pt, SimpleITK.sitkFloat32)
+#    SimpleITK.WriteImage(pt,'/tmp/pt.mhd')
+    test_label_bck()