diff --git a/src/mednet/libs/segmentation/config/models/unet.py b/src/mednet/libs/segmentation/config/models/unet.py
index 498f6324f1eeb775742b7b9c261bbbd19ca93df7..10859a6775ebcdba73e471e6e731677125c49b8f 100644
--- a/src/mednet/libs/segmentation/config/models/unet.py
+++ b/src/mednet/libs/segmentation/config/models/unet.py
@@ -1,12 +1,16 @@
 # SPDX-FileCopyrightText: Copyright © 2024 Idiap Research Institute <contact@idiap.ch>
 #
 # SPDX-License-Identifier: GPL-3.0-or-later
-"""Little W-Net for image segmentation.
 
-The Little W-Net architecture contains roughly around 70k parameters and
-closely matches (or outperforms) other more complex techniques.
+"""U-Net for image segmentation.
 
-Reference: [GALDRAN-2020]_
+U-Net is a convolutional neural network that was developed for biomedical image
+segmentation at the Computer Science Department of the University of Freiburg,
+Germany.  The network is based on the fully convolutional network (FCN) and its
+architecture was modified and extended to work with fewer training images and
+to yield more precise segmentations.
+
+Reference: [RONNEBERGER-2015]_
 """
 
 from mednet.libs.segmentation.engine.adabound import AdaBound