Add minimun spot diameter as parameter

2d_spots_in_fibers.py

@@ -7,7 +7,7 @@
 #@ 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
 #@ String (label="Spot detection quality threshold", description="comma separated list of values, one per channel", value="80,80,80,80" ) quality_thresholds_string
-
+#@ Double (label="Minimum spot diameter", description="smaller spots will be discarded, value=5, min=1, max=200, stepSize=0.5, persist=false, style=slider) spot_diameter
 
 # trackmate imports
 from fiji.plugin.trackmate import Settings
@@ -274,7 +274,7 @@ def BFopen_image(path_to_image, channel_number, series_number, region=None, z_sl
     return imps[0]
 
 
-def run_trackmate_dog_spot_detector(imp, quality_threshold):
+def run_trackmate_dog_spot_detector(imp, spot_diameter, quality_threshold):
     """Run TrackMates DoG detector with a given quality threshold
     on a target image
 
@@ -296,7 +296,7 @@ def run_trackmate_dog_spot_detector(imp, quality_threshold):
 
     settings.detectorFactory = DogDetectorFactory()
     settings.detectorSettings['DO_SUBPIXEL_LOCALIZATION'] = True
-    settings.detectorSettings['RADIUS'] = 0.15 # type = double
+    settings.detectorSettings['RADIUS'] = spot_diameter / 2 # type = double
     settings.detectorSettings['TARGET_CHANNEL'] = 0
     settings.detectorSettings['THRESHOLD'] = quality_threshold # type = double
     settings.detectorSettings['DO_MEDIAN_FILTERING'] = False
@@ -758,18 +758,16 @@ processing_channels = processing_channels_string.split(",")
 quality_thresholds_string = quality_thresholds_string.replace(" ", "")
 quality_thresholds = quality_thresholds_string.split(",")
 
-# 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)
 if threshold <= 0:
     threshold = get_threshold_from_method(dapi_channel, "otsu")
 dapi_binary = convert_to_binary(dapi_channel, threshold)
-close_images([dapi_channel])
+
+# Get the fiber segmentation from ij roizip and convert to labelimage
+load_rois_from_zip(fiber_segmentation_roiset)
+fibers_label_imp = convert_rois_to_labelimage(dapi_channel)
+dapi_channel.close()
 
 # detect spots and count them per fiber
 results_table = ResultsTable()