diff --git a/clinicadl/quality_check/t1_volume/quality_check.py b/clinicadl/quality_check/t1_volume/quality_check.py
index 9e9262605..166350614 100644
--- a/clinicadl/quality_check/t1_volume/quality_check.py
+++ b/clinicadl/quality_check/t1_volume/quality_check.py
@@ -9,12 +9,11 @@
 
 import pandas as pd
 
-from .utils import extract_metrics
+from clinicadl.quality_check.t1_volume.utils import extract_metrics
 
 
 def quality_check(caps_dir: Path, output_directory: Path, group_label):
     logger = getLogger("clinicadl.quality_check")
-
     extract_metrics(
         caps_dir=caps_dir, output_dir=output_directory, group_label=group_label
     )
@@ -22,7 +21,6 @@ def quality_check(caps_dir: Path, output_directory: Path, group_label):
         f"Quality check metrics extracted at {output_directory / 'QC_metrics.tsv'}."
     )
     qc_df = pd.read_csv(output_directory / "QC_metrics.tsv", sep="\t")
-
     rejection1_df = qc_df[qc_df.max_intensity > 0.95]
     rejection1_df.to_csv(output_directory / "pass_step-1.tsv", sep="\t", index=False)
     logger.info(
diff --git a/clinicadl/quality_check/t1_volume/utils.py b/clinicadl/quality_check/t1_volume/utils.py
index 79677e78b..2ace21ccd 100644
--- a/clinicadl/quality_check/t1_volume/utils.py
+++ b/clinicadl/quality_check/t1_volume/utils.py
@@ -63,11 +63,15 @@ def extract_metrics(caps_dir: Path, output_dir: Path, group_label):
     results_df = pd.DataFrame(columns=columns)
 
     subjects = list((caps_dir / "subjects").iterdir())
-    subjects = [subject for subject in subjects if str(subject)[:4:] == "sub-"]
+    subjects = [
+        subject.stem for subject in subjects if str(subject.stem)[:4:] == "sub-"
+    ]
     for subject in subjects:
         subject_path = caps_dir / "subjects" / subject
         sessions = list(subject_path.iterdir())
-        sessions = [session for session in sessions if str(session)[:4:] == "ses-"]
+        sessions = [
+            session.stem for session in sessions if str(session.stem)[:4:] == "ses-"
+        ]
         for session in sessions:
             image_path = (
                 subject_path
@@ -76,12 +80,13 @@ def extract_metrics(caps_dir: Path, output_dir: Path, group_label):
                 / "spm"
                 / "segmentation"
                 / "normalized_space"
-                / subject
-                + "_"
-                + session
-                + "_T1w_segm-graymatter_space-Ixi549Space_modulated-off_probability.nii.gz"
+                / (
+                    subject
+                    + "_"
+                    + session
+                    + "_T1w_segm-graymatter_space-Ixi549Space_modulated-off_probability.nii.gz"
+                )
             )
-
             if image_path.is_file():
                 # GM analysis
                 image_nii = nib.load(image_path)