diff --git a/logics.py b/logics.py
index 977addb..502456d 100644
--- a/logics.py
+++ b/logics.py
@@ -28,14 +28,15 @@
 
 class DiffractionLimitedAnalysis:
 
-    def __init__(self, data_path):
+    def __init__(self, data_path, parameters):
 
         self.error = 1 # When this value is 1, no error was detected in the object.
         self.path_program = os.path.dirname(__file__)
         self.path_data_main = data_path
+        self.parameters = parameters
 
         # Construct dirs for results
-        self.path_result_main = data_path + '_results'
+        self.path_result_main = data_path + '_results' + self.parameters
         if os.path.isdir(self.path_result_main) != 1:
             os.mkdir(self.path_result_main)
         self.path_result_raw = os.path.join(self.path_result_main, 'raw')
@@ -144,8 +145,8 @@ def call_ComDet(self, size, threshold, progress_signal=None, IJ=None):
                print('No spot found in FoV: ' + field)
             else:
                 img_dimensions = Image.open(imgFile).size
-                df = df.loc[(df['X_(px)'] >= img_dimensions[0] * 0.05) & (df['X_(px)'] <= img_dimensions[0] * 0.95)]
-                df = df.loc[(df['Y_(px)'] >= img_dimensions[1] * 0.05) & (df['Y_(px)'] <= img_dimensions[1] * 0.95)]
+                df = df.loc[(df['X_(px)'] >= img_dimensions[0] * 0.02) & (df['X_(px)'] <= img_dimensions[0] * 0.98)]
+                df = df.loc[(df['Y_(px)'] >= img_dimensions[1] * 0.02) & (df['Y_(px)'] <= img_dimensions[1] * 0.98)]
                 # Remove particles detected in the 5% pixels from the edges
                 df = df.reset_index(drop=True)
                 df.to_csv(saveto + '_results.csv')
@@ -368,7 +369,15 @@ def generate_reports(self, progress_signal=None):
                 })
                 summary_report = pd.concat([summary_report, df_sum])
             except pd.errors.EmptyDataError:
-                pass
+                df_sum = pd.DataFrame.from_dict({
+                    'Well': [well],
+                    'NoOfFoV': [len(self.wells[well])],
+                    'ParticlePerFoV': [0],
+                    'MeanSize': [0],
+                    'MeanIntegrInt': [0],
+                    'MeanIntPerArea': [0]
+                })
+                summary_report = pd.concat([summary_report, df_sum])
             if progress_signal == None:
                 pass
             else:
diff --git a/main.py b/main.py
index 0d3dc46..f0734fc 100755
--- a/main.py
+++ b/main.py
@@ -156,11 +156,11 @@ def clickDFLSPRun(self):
 
     def clickDFLSPGenerateReports(self):
         data_path = self.window.DFLSP_pathEntry.text()
-        self.data_path = data_path.replace('_results', '')
+        self.data_path = data_path.replace('_results' + self.parameters, '')
         self.window.DFLSP_pathEntry.setText(self.data_path)
         guard = self._checkDFLSPParameters()
         if guard == 1:
-            if os.path.isdir(self.data_path + '_results') ==False:
+            if os.path.isdir(self.data_path + '_results' + self.parameters) ==False:
                 self.showMessage('w', 'This dataset has not been analysed. Please run analysis.')
             else:
 
@@ -170,11 +170,11 @@ def clickDFLSPGenerateReports(self):
 
     def clickDFLSPReadTaggedResults(self):
         data_path = self.window.DFLSP_pathEntry.text()
-        self.data_path = data_path.replace('_results', '')
+        self.data_path = data_path.replace('_results' + self.parameters, '')
         self.window.DFLSP_pathEntry.setText(self.data_path)
         guard = self._checkDFLSPParameters()
         if guard == 1:
-            if os.path.isdir(self.data_path + '_results') ==False:
+            if os.path.isdir(self.data_path + '_results' + self.parameters) ==False:
                 self.showMessage('w', 'This dataset has not been analysed. Please run analysis.')
             else:
                 self.updateLog('Data path set to '+data_path)
@@ -194,6 +194,9 @@ def _checkDFLSPParameters(self):
             self.window.DFLSP_pathEntry.setText(self.data_path)
             self.updateLog('Data path set to '+data_path)
 
+        # Get the method for analysis
+        self.method = self.window.DFLSP_methodSelector.currentText()
+
         # Check input: threshold
         try:
             self.threshold = int(self.window.DFLSP_thresholdEntry.text())
@@ -218,7 +221,8 @@ def _checkDFLSPParameters(self):
         else:
             self.updateLog('Estimated particle size set as '+str(self.size)+' pixels.')
 
-        self.project = DiffractionLimitedAnalysis(self.data_path) # Creat DiffractionLimitedAnalysis object
+        self.parameters = '_' + self.method + '_' + str(self.threshold) + '_' + str(self.size)
+        self.project = DiffractionLimitedAnalysis(self.data_path, self.parameters) # Creat DiffractionLimitedAnalysis object
         if self.project.error == 1:
             return 1
         else:
@@ -231,7 +235,7 @@ def _runDFLSPAnalysis(self):
         # Create a QThread object
         self.PFThread = QThread()
         # Create a worker object
-        self.particleFinder = toolbox.DFLParticleFinder(self.window.DFLSP_methodSelector.currentText(), self.project, self.size, self.threshold, self.IJ)
+        self.particleFinder = toolbox.DFLParticleFinder(self.method, self.project, self.size, self.threshold, self.IJ)
 
         # Connect signals and slots
         self.PFThread.started.connect(self.particleFinder.run)