Adapt to new function

2d_spots_in_fibers.py

@@ -485,16 +485,17 @@ for index, channel in enumerate(processing_channels):
     spots_binary_imp = convert_labelimage_to_binary(spots_label_imp)
     dapi_positive_spots_binary = ImageCalculator.run(spots_binary_imp, dapi_binary, "Multiply create")
     dapi_negative_spots_binary = ImageCalculator.run(spots_binary_imp, dapi_positive_spots_binary, "Subtract create")
-
-    n_spots_per_fiber = measure_intensity_sum(fibers_label_imp, spots_binary_imp)
-    n_dapi_positive_spots_per_fiber = measure_intensity_sum(fibers_label_imp, dapi_positive_spots_binary)
-    n_dapi_negative_spots_per_fiber = measure_intensity_sum(fibers_label_imp, dapi_negative_spots_binary)
+    
+    load_rois_from_zip(fiber_segmentation_roiset)
+    fiber_label_IDs, n_spots_per_fiber = measure_intensity_sum(spots_binary_imp, rm)
+    _, n_dapi_positive_spots_per_fiber = measure_intensity_sum(dapi_positive_spots_binary, rm)
+    _, n_dapi_negative_spots_per_fiber = measure_intensity_sum(dapi_negative_spots_binary, rm)
 
     # TODO: the column fiber label ID needs to be added only one time. Maybe check before if column exists.
-    add_results_to_resultstable(results_table, "fiber label ID", n_spots_per_fiber[0])
-    add_results_to_resultstable(results_table, "n spots channel " + str(channel), n_spots_per_fiber[1])
-    add_results_to_resultstable(results_table, "n spots dapi positive channel " + str(channel), n_dapi_positive_spots_per_fiber[1])
-    add_results_to_resultstable(results_table, "n spots dapi negative channel " + str(channel), n_dapi_negative_spots_per_fiber[1])
+    add_results_to_resultstable(results_table, "fiber label ID", fiber_label_IDs)
+    add_results_to_resultstable(results_table, "n spots channel " + str(channel), n_spots_per_fiber)
+    add_results_to_resultstable(results_table, "n spots dapi positive channel " + str(channel), n_dapi_positive_spots_per_fiber)
+    add_results_to_resultstable(results_table, "n spots dapi negative channel " + str(channel), n_dapi_negative_spots_per_fiber)
     close_images([spots_channel, spots_label_imp, spots_binary_imp, spots_binary_imp, dapi_binary, dapi_positive_spots_binary, dapi_negative_spots_binary])
 
 results_table.show("Spots")