2d_spots_in_fibers.py

@@ -2,7 +2,7 @@
 #@ CommandService command
 #@ File (label="select image", description="select your input image", style=file) path_to_image
 #@ Integer (label="select image file series", description="leave 1 if not needed", value=1, min=1, max=20, stepSize=1, persist=false, style=slider) series_number
-#@ Integer (label="Fiber Segmentation", description="select the Fiber Segmentation RoiSet .zip file") fiber_segmentation_roiset
+#@ File (label="Fiber Segmentation", description="select the Fiber Segmentation RoiSet .zip file", style=file) fiber_segmentation_roiset
 #@ Integer (label="DAPI channel", description="select the DAPI channel", min=1, max=20, stepSize=1, persist=true, style=slider) dapi_channel_number
 #@ Integer (label="DAPI threshold", description="0 = Auto", min=0) threshold
 #@ String (label="processing channels", description="comma separated list of channels, e.g. 2,3,6,7", value="1,2,3,4") processing_channels_string
@@ -36,7 +36,7 @@ from net.imglib2.roi import Regions
 from net.imglib2.roi.labeling import LabelRegions
 from net.imglib2.algorithm.labeling import ConnectedComponents
 # BIOP imports
-from ch.epfl.biop.ij2command import Labels2Rois
+from ch.epfl.biop.ij2command import Labels2Rois, Rois2Labels
 # python imports
 import os
 
@@ -707,6 +707,33 @@ def save_labelimage_as_ijroiset(label_imp, filename, suffix, target):
     rm.reset()
 
 
+def load_rois_from_zip(path):
+    """Load ROIs from the given zip file and add them to the RoiManager.
+
+    Parameters
+    ----------
+    path : string
+        Path to the ROI zip file.
+    """
+    rm = RoiManager.getInstance()
+    if not rm:
+        rm = RoiManager()
+    rm.reset()
+
+    rm.runCommand("Open", path)
+
+
+def convert_rois_to_labelimage(imp):
+    rm = RoiManager.getInstance()
+    if not rm:
+        rm = RoiManager()
+
+    label_imp = command.run( Rois2Labels , False , 'imp' , imp , 'rm', rm).get().getOutput("label_imp")
+    rm.reset() # TODO: should be optional but can be default
+
+    return label_imp
+
+
 def close_images(list_of_imps):
     """Close given ImagePlus images
 
@@ -721,6 +748,7 @@ def close_images(list_of_imps):
 
 
 path_to_image = str(path_to_image).replace("\\","/")
+fiber_segmentation_roiset = str(fiber_segmentation_roiset).replace("\\","/")
 parent_dir, filename, ext = get_parentdir_filename_ext_from_path(path_to_image)
 write_bf_memoryfile(path_to_image)
 n_channels, image_width, image_height, bit_depth = get_ome_metadata(path_to_image, series_number)
@@ -729,10 +757,14 @@ processing_channels = processing_channels_string.split(",")
 quality_thresholds_string = quality_thresholds_string.replace(" ", "")
 quality_thresholds = quality_thresholds_string.split(",")
 
-# TODO: Get the fiber segmentation and convert to labelimage
+# Get the fiber segmentation from ij roizip and convert to labelimage
+canvas = create_empty_image(32, image_width, image_height)
+load_rois_from_zip(fiber_segmentation_roiset)
+fibers_label_imp = convert_rois_to_labelimage(canvas)
+canvas.close()
 
 # threshold DAPI channel and convert to binary
-dapi_channel = BFopen_image(path_to_image, dapi_channel_number, series_number, z_slice_number=dapi_channel_zslice)
+dapi_channel = BFopen_image(path_to_image, dapi_channel_number, series_number)
 if threshold <= 0:
     threshold = get_threshold_from_method(dapi_channel, "otsu")
 dapi_binary = convert_to_binary(dapi_channel, threshold)
@@ -743,16 +775,15 @@ results_table = ResultsTable()
 for index, channel in enumerate(processing_channels):
     channel = int(channel)
     quality_threshold = float(quality_thresholds[index])
-    spots_channel = BFopen_image(path_to_image, channel, series_number) # can be a stack
-    spots_label_imp = run_trackmate_dog_spot_detector(spots_channel, quality_threshold) # spot detection is 3D
+    spots_channel = BFopen_image(path_to_image, channel, series_number)
+    spots_label_imp = run_trackmate_dog_spot_detector(spots_channel, quality_threshold)
     save_image_as_IJtif(spots_label_imp, filename, "spots_ch" + str(channel), parent_dir)
     save_labelimage_as_ijroiset(spots_label_imp, filename, "spots_ch" + str(channel), parent_dir)
-    spots_binary_imp = convert_labelimage_to_binary(spots_label_imp) # can be a stack
-    spots_binary_imp_sum_proj = ZProjector.run(spots_binary_imp, "sum") # if 2 (n) spots perfecly overlap in z, the pixel value will be 2 (n)
-    dapi_positive_spots_binary = ImageCalculator.run(spots_binary_imp_sum_proj, dapi_binary, "Multiply create")
-    dapi_negative_spots_binary = ImageCalculator.run(spots_binary_imp_sum_proj, dapi_positive_spots_binary, "Subtract create")
+    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_sum_proj)
+    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)
 
@@ -761,7 +792,7 @@ for index, channel in enumerate(processing_channels):
     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])
-    close_images([spots_channel, spots_label_imp, spots_binary_imp, spots_binary_imp_sum_proj, dapi_binary, dapi_positive_spots_binary, dapi_negative_spots_binary])
+    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")
 save_results_table(results_table, filename, "Spots", parent_dir)