diff --git a/spindle_tracker/io/trackmate.py b/spindle_tracker/io/trackmate.py
index 7298641..e081ecc 100644
--- a/spindle_tracker/io/trackmate.py
+++ b/spindle_tracker/io/trackmate.py
@@ -1,5 +1,7 @@
+import itertools
 import xml.etree.cElementTree as et
 
+import networkx as nx
 import pandas as pd
 import numpy as np
 
@@ -27,15 +29,14 @@ def trackmate_peak_import(trackmate_xml_path, get_tracks=False):
                      'ESTIMATED_DIAMETER': 'w',
                      'QUALITY': 'q',
                      'ID': 'spot_id',
-                     # 'MEAN_INTENSITY': 'mean_intensity',
+                     'MEAN_INTENSITY': 'mean_intensity',
                      'MEDIAN_INTENSITY': 'median_intensity',
                      'MIN_INTENSITY': 'min_intensity',
                      'MAX_INTENSITY': 'max_intensity',
                      'TOTAL_INTENSITY': 'total_intensity',
                      'STANDARD_DEVIATION': 'std_intensity',
                      'CONTRAST': 'contrast',
-                     'SNR': 'snr',}
-
+                     'SNR': 'snr'}
 
     features = root.find('Model').find('FeatureDeclarations').find('SpotFeatures')
     features = [c.get('feature') for c in features.getchildren()] + ['ID']
@@ -80,27 +81,59 @@ def trackmate_peak_import(trackmate_xml_path, get_tracks=False):
     if get_tracks:
         filtered_track_ids = [int(track.get('TRACK_ID')) for track in root.find('Model').find('FilteredTracks').findall('TrackID')]
 
-        trajs['label'] = np.nan
+        new_trajs = pd.DataFrame()
+        label_id = 0
         trajs = trajs.set_index('spot_id')
 
         tracks = root.find('Model').find('AllTracks')
         for track in tracks.findall('Track'):
-            track_id = int(track.get("TRACK_ID"))
 
+            track_id = int(track.get("TRACK_ID"))
             if track_id in filtered_track_ids:
 
-                spot_ids = []
-                for edge in track.findall('Edge'):
-                    spot_ids.append(int(edge.get('SPOT_SOURCE_ID')))
-                    spot_ids.append(int(edge.get('SPOT_TARGET_ID')))
+                spot_ids = [(edge.get('SPOT_SOURCE_ID'), edge.get('SPOT_TARGET_ID'), edge.get('EDGE_TIME')) for edge in track.findall('Edge')]
+                spot_ids = np.array(spot_ids).astype('float')
+                spot_ids = pd.DataFrame(spot_ids, columns=['source', 'target', 'time'])
+                spot_ids = spot_ids.sort_values(by='time')
+                spot_ids = spot_ids.set_index('time')
+
+                # Build graph
+                graph = nx.Graph()
+                for t, spot in spot_ids.iterrows():
+                    graph.add_edge(int(spot['source']), int(spot['target']), attr_dict=dict(t=t))
+
+                # Find graph extremities by checking if number of neighbors is equal to 1
+                tracks_extremities = [node for node in graph.nodes() if len(graph.neighbors(node)) == 1]
+
+                paths = []
+                # Find all possible paths between extremities
+                for source, target in itertools.combinations(tracks_extremities, 2):
+
+                    # Find all path between two nodes
+                    for path in nx.all_simple_paths(graph, source=source, target=target):
+
+                        # Now we need to check wether this path respect the time logic contraint
+                        # edges can only go in one direction of the time
+
+                        # Build times vector according to path
+                        t = []
+                        for i, node_srce in enumerate(path[:-1]):
+                            node_trgt = path[i+1]
+                            t.append(graph.edge[node_srce][node_trgt]['t'])
+
+                        # Will be equal to 1 if going to one time direction
+                        if len(np.unique(np.sign(np.diff(t)))) == 1:
+                            paths.append(path)
 
-                spot_ids = np.unique(spot_ids)
-                trajs.loc[spot_ids, 'label'] = track_id
+                # Add each individual trajectory to a new DataFrame called new_trajs
+                for path in paths:
+                    traj = trajs.loc[path].copy()
+                    traj['label'] = label_id
+                    label_id += 1
 
-        trajs = trajs.reset_index()
+                    new_trajs = new_trajs.append(traj)
 
-        # Remove spot without labels
-        trajs = trajs.dropna(subset=['label'])
+        trajs = new_trajs
 
     trajs.set_index(['t_stamp', 'label'], inplace=True)
     trajs = trajs.sort_index()