diff --git a/helpers/extract_hdf5_images.py b/helpers/extract_hdf5_images.py
index a093412d6d6a8e2a50b45ac620fc5b65d95e525e..61c79c912ac47aa2d3b035ced0938f114d12d7c6 100644
--- a/helpers/extract_hdf5_images.py
+++ b/helpers/extract_hdf5_images.py
@@ -23,8 +23,8 @@ def extract_images_from_hdf5(hdf5_file):
     return tensors_dict
 
 
-def get_hdf5_files(directory, recursive=False) -> list[pathlib.Path]:
-    return directory.glob("**/*.hdf5", recursive=recursive)
+def get_hdf5_files(directory) -> list[pathlib.Path]:
+    return directory.glob("**/*.hdf5")
 
 
 def main():
@@ -34,16 +34,10 @@ def main():
         type=pathlib.Path,
         help="Directory in which hdf5 files are located.",
     )
-    parser.add_argument(
-        "--recursive",
-        "-r",
-        action="store_true",
-        help="Set to true to search recursively in the input directory.",
-    )
 
     args = parser.parse_args()
 
-    hdf5_files = get_hdf5_files(args.input_dir, recursive=args.recursive)
+    hdf5_files = get_hdf5_files(args.input_dir)
     for hdf5_file in hdf5_files:
         tensors_dict = extract_images_from_hdf5(hdf5_file)
 
diff --git a/pyproject.toml b/pyproject.toml
index 5d2bcc6476083cfb7021e5ced001344a0d2e08a4..0be3495ef1bda54fe004d446c5d2f0b47fdc0591 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -425,6 +425,8 @@ lwnet = "mednet.libs.segmentation.config.models.lwnet"
 
 # drive dataset - retinal vessel segmentation
 drive = "mednet.libs.segmentation.config.data.drive.default"
+stare = "mednet.libs.segmentation.config.data.stare.ah"
+stare-2nd = "mednet.libs.segmentation.config.data.stare.vk"
 
 [tool.ruff]
 line-length = 88
diff --git a/src/mednet/libs/segmentation/config/data/stare/__init__.py b/src/mednet/libs/segmentation/config/data/stare/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/src/mednet/libs/segmentation/config/data/stare/ah.json b/src/mednet/libs/segmentation/config/data/stare/ah.json
new file mode 100644
index 0000000000000000000000000000000000000000..1192d3feebe368d831c8f7444e6303e1427988bc
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/stare/ah.json
@@ -0,0 +1,106 @@
+{
+ "train": [
+  [
+   "stare-images/im0001.ppm",
+   "labels-ah/im0001.ah.ppm",
+   "stare-images/im0001.png"
+  ],
+  [
+   "stare-images/im0002.ppm",
+   "labels-ah/im0002.ah.ppm",
+   "stare-images/im0002.png"
+  ],
+  [
+   "stare-images/im0003.ppm",
+   "labels-ah/im0003.ah.ppm",
+   "stare-images/im0003.png"
+  ],
+  [
+   "stare-images/im0004.ppm",
+   "labels-ah/im0004.ah.ppm",
+   "stare-images/im0004.png"
+  ],
+  [
+   "stare-images/im0005.ppm",
+   "labels-ah/im0005.ah.ppm",
+   "stare-images/im0005.png"
+  ],
+  [
+   "stare-images/im0044.ppm",
+   "labels-ah/im0044.ah.ppm",
+   "stare-images/im0044.png"
+  ],
+  [
+   "stare-images/im0077.ppm",
+   "labels-ah/im0077.ah.ppm",
+   "stare-images/im0077.png"
+  ],
+  [
+   "stare-images/im0081.ppm",
+   "labels-ah/im0081.ah.ppm",
+   "stare-images/im0081.png"
+  ],
+  [
+   "stare-images/im0082.ppm",
+   "labels-ah/im0082.ah.ppm",
+   "stare-images/im0082.png"
+  ],
+  [
+   "stare-images/im0139.ppm",
+   "labels-ah/im0139.ah.ppm",
+   "stare-images/im0139.png"
+  ]
+ ],
+ "test": [
+  [
+   "stare-images/im0162.ppm",
+   "labels-ah/im0162.ah.ppm",
+   "stare-images/im0162.png"
+  ],
+  [
+   "stare-images/im0163.ppm",
+   "labels-ah/im0163.ah.ppm",
+   "stare-images/im0163.png"
+  ],
+  [
+   "stare-images/im0235.ppm",
+   "labels-ah/im0235.ah.ppm",
+   "stare-images/im0235.png"
+  ],
+  [
+   "stare-images/im0236.ppm",
+   "labels-ah/im0236.ah.ppm",
+   "stare-images/im0236.png"
+  ],
+  [
+   "stare-images/im0239.ppm",
+   "labels-ah/im0239.ah.ppm",
+   "stare-images/im0239.png"
+  ],
+  [
+   "stare-images/im0240.ppm",
+   "labels-ah/im0240.ah.ppm",
+   "stare-images/im0240.png"
+  ],
+  [
+   "stare-images/im0255.ppm",
+   "labels-ah/im0255.ah.ppm",
+   "stare-images/im0255.png"
+  ],
+  [
+   "stare-images/im0291.ppm",
+   "labels-ah/im0291.ah.ppm",
+   "stare-images/im0291.png"
+  ],
+  [
+   "stare-images/im0319.ppm",
+   "labels-ah/im0319.ah.ppm",
+   "stare-images/im0319.png"
+  ],
+  [
+   "stare-images/im0324.ppm",
+   "labels-ah/im0324.ah.ppm",
+   "stare-images/im0324.png"
+  ]
+ ]
+}
diff --git a/src/mednet/libs/segmentation/config/data/stare/ah.py b/src/mednet/libs/segmentation/config/data/stare/ah.py
new file mode 100644
index 0000000000000000000000000000000000000000..cf6051a10585ae245a086e8223ffbd0d716c35a2
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/stare/ah.py
@@ -0,0 +1,6 @@
+# SPDX-FileCopyrightText: Copyright © 2024 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+from mednet.libs.segmentation.config.data.stare.datamodule import DataModule
+
+datamodule = DataModule("ah.json")
diff --git a/src/mednet/libs/segmentation/config/data/stare/datamodule.py b/src/mednet/libs/segmentation/config/data/stare/datamodule.py
new file mode 100644
index 0000000000000000000000000000000000000000..5fc90042b6c34d06ae1e780e27c3cb30f16698b8
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/stare/datamodule.py
@@ -0,0 +1,128 @@
+# SPDX-FileCopyrightText: Copyright © 2024 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+"""STARE dataset for Vessel Segmentation."""
+
+import importlib.resources
+import os
+from pathlib import Path
+
+import PIL.Image
+import pkg_resources
+from mednet.libs.common.data.datamodule import CachingDataModule
+from mednet.libs.common.data.split import JSONDatabaseSplit
+from mednet.libs.common.data.typing import DatabaseSplit, Sample
+from mednet.libs.segmentation.data.typing import (
+    SegmentationRawDataLoader as _SegmentationRawDataLoader,
+)
+from torchvision import tv_tensors
+from torchvision.transforms.functional import to_tensor
+
+from ....utils.rc import load_rc
+
+CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
+"""Key to search for in the configuration file for the root directory of this
+database."""
+
+
+class SegmentationRawDataLoader(_SegmentationRawDataLoader):
+    """A specialized raw-data-loader for the Stare dataset."""
+
+    datadir: str
+    """This variable contains the base directory where the database raw data is
+    stored."""
+
+    def __init__(self):
+        self.datadir = load_rc().get(
+            CONFIGURATION_KEY_DATADIR, os.path.realpath(os.curdir)
+        )
+        self._pkg_path = pkg_resources.resource_filename(__name__, "masks")
+
+    def sample(self, sample: tuple[str, str, str]) -> Sample:
+        """Load a single image sample from the disk.
+
+        Parameters
+        ----------
+        sample
+            A tuple containing the path suffix, within the dataset root folder,
+            where to find the image to be loaded, and an integer, representing the
+            sample label.
+
+        Returns
+        -------
+            The sample representation.
+        """
+
+        image = PIL.Image.open(Path(self.datadir) / str(sample[0])).convert(
+            mode="RGB"
+        )
+        tensor = tv_tensors.Image(to_tensor(image))
+        target = tv_tensors.Image(
+            to_tensor(
+                PIL.Image.open(Path(self.datadir) / str(sample[1])).convert(
+                    mode="1", dither=None
+                )
+            )
+        )
+        mask = tv_tensors.Mask(
+            to_tensor(
+                PIL.Image.open(Path(self._pkg_path) / str(sample[2])).convert(
+                    mode="1", dither=None
+                )
+            )
+        )
+
+        return tensor, dict(target=target, mask=mask, name=sample[0])  # type: ignore[arg-type]
+
+
+def make_split(basename: str) -> DatabaseSplit:
+    """Return a database split for the Stare database.
+
+    Parameters
+    ----------
+    basename
+        Name of the .json file containing the split to load.
+
+    Returns
+    -------
+        An instance of DatabaseSplit.
+    """
+
+    return JSONDatabaseSplit(
+        importlib.resources.files(__name__.rsplit(".", 1)[0]).joinpath(basename)
+    )
+
+
+class DataModule(CachingDataModule):
+    """STARE dataset for Vessel Segmentation.
+
+    A subset of the original STARE dataset contains 20 annotated eye fundus images
+    with a resolution of 700 x 605 (width x height). Two sets of ground-truth
+    vessel annotations are available. The first set by Adam Hoover ("ah") is
+    commonly used for training and testing. The second set by Valentina Kouznetsova
+    ("vk") is typically used as a “human” baseline.
+
+    * Reference: [STARE-2000]_
+    * Original resolution (width x height): 700 x 605
+    * Split reference: [MANINIS-2016]_
+    * Protocol ``ah`` (default baseline):
+
+    * Training samples: 10 (including labels from annotator "ah")
+    * Test samples: 10 (including labels from annotator "ah")
+
+    * Protocol ``vk`` (normally used as human comparison):
+
+    * Training samples: 10 (including labels from annotator "vk")
+    * Test samples: 10 (including labels from annotator "vk")
+
+    Parameters
+    ----------
+    split_filename
+        Name of the .json file containing the split to load.
+    """
+
+    def __init__(self, split_filename: str):
+        super().__init__(
+            database_split=make_split(split_filename),
+            raw_data_loader=SegmentationRawDataLoader(),
+        )
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0001.png b/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0001.png
new file mode 100644
index 0000000000000000000000000000000000000000..a168919fce790aa441e8f44653ee940f0cc16267
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new file mode 100644
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index 0000000000000000000000000000000000000000..27ad8cdfee613c4afc44126c95d4714ff67a13a9
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diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0324.png b/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0324.png
new file mode 100644
index 0000000000000000000000000000000000000000..1d7a5a616fbbd0bc99f4fe69a20e940f8d6c7308
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diff --git a/src/mednet/libs/segmentation/config/data/stare/vk.json b/src/mednet/libs/segmentation/config/data/stare/vk.json
new file mode 100644
index 0000000000000000000000000000000000000000..3af0c7834596b798b348120446c36062af81eb52
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/stare/vk.json
@@ -0,0 +1,106 @@
+{
+ "train": [
+  [
+   "stare-images/im0001.ppm",
+   "labels-vk/im0001.vk.ppm",
+   "stare-images/im0001.png"
+  ],
+  [
+   "stare-images/im0002.ppm",
+   "labels-vk/im0002.vk.ppm",
+   "stare-images/im0002.png"
+  ],
+  [
+   "stare-images/im0003.ppm",
+   "labels-vk/im0003.vk.ppm",
+   "stare-images/im0003.png"
+  ],
+  [
+   "stare-images/im0004.ppm",
+   "labels-vk/im0004.vk.ppm",
+   "stare-images/im0004.png"
+  ],
+  [
+   "stare-images/im0005.ppm",
+   "labels-vk/im0005.vk.ppm",
+   "stare-images/im0005.png"
+  ],
+  [
+   "stare-images/im0044.ppm",
+   "labels-vk/im0044.vk.ppm",
+   "stare-images/im0044.png"
+  ],
+  [
+   "stare-images/im0077.ppm",
+   "labels-vk/im0077.vk.ppm",
+   "stare-images/im0077.png"
+  ],
+  [
+   "stare-images/im0081.ppm",
+   "labels-vk/im0081.vk.ppm",
+   "stare-images/im0081.png"
+  ],
+  [
+   "stare-images/im0082.ppm",
+   "labels-vk/im0082.vk.ppm",
+   "stare-images/im0082.png"
+  ],
+  [
+   "stare-images/im0139.ppm",
+   "labels-vk/im0139.vk.ppm",
+   "stare-images/im0139.png"
+  ]
+ ],
+ "test": [
+  [
+   "stare-images/im0162.ppm",
+   "labels-vk/im0162.vk.ppm",
+   "stare-images/im0162.png"
+  ],
+  [
+   "stare-images/im0163.ppm",
+   "labels-vk/im0163.vk.ppm",
+   "stare-images/im0163.png"
+  ],
+  [
+   "stare-images/im0235.ppm",
+   "labels-vk/im0235.vk.ppm",
+   "stare-images/im0235.png"
+  ],
+  [
+   "stare-images/im0236.ppm",
+   "labels-vk/im0236.vk.ppm",
+   "stare-images/im0236.png"
+  ],
+  [
+   "stare-images/im0239.ppm",
+   "labels-vk/im0239.vk.ppm",
+   "stare-images/im0239.png"
+  ],
+  [
+   "stare-images/im0240.ppm",
+   "labels-vk/im0240.vk.ppm",
+   "stare-images/im0240.png"
+  ],
+  [
+   "stare-images/im0255.ppm",
+   "labels-vk/im0255.vk.ppm",
+   "stare-images/im0255.png"
+  ],
+  [
+   "stare-images/im0291.ppm",
+   "labels-vk/im0291.vk.ppm",
+   "stare-images/im0291.png"
+  ],
+  [
+   "stare-images/im0319.ppm",
+   "labels-vk/im0319.vk.ppm",
+   "stare-images/im0319.png"
+  ],
+  [
+   "stare-images/im0324.ppm",
+   "labels-vk/im0324.vk.ppm",
+   "stare-images/im0324.png"
+  ]
+ ]
+}
diff --git a/src/mednet/libs/segmentation/config/data/stare/vk.py b/src/mednet/libs/segmentation/config/data/stare/vk.py
new file mode 100644
index 0000000000000000000000000000000000000000..f4c88abc6cd2d54ac376f9fa9a5597fcd791bd77
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/stare/vk.py
@@ -0,0 +1,6 @@
+# SPDX-FileCopyrightText: Copyright © 2024 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+from mednet.libs.segmentation.config.data.stare.datamodule import DataModule
+
+datamodule = DataModule("vk.json")
diff --git a/src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_stare_ah.json b/src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_stare_ah.json
new file mode 100644
index 0000000000000000000000000000000000000000..aa9585edc780fbae5bd324ee677e74978112f3a9
--- /dev/null
+++ b/src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_stare_ah.json
@@ -0,0 +1,16 @@
+{
+  "train": [
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+}
diff --git a/src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_stare_ah.json b/src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_stare_ah.json
new file mode 100644
index 0000000000000000000000000000000000000000..901cb9aee6d78efea366cedf676e45f0977fd33c
--- /dev/null
+++ b/src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_stare_ah.json
@@ -0,0 +1,16 @@
+{
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+  ]
+}
diff --git a/src/mednet/libs/segmentation/tests/test_stare.py b/src/mednet/libs/segmentation/tests/test_stare.py
new file mode 100644
index 0000000000000000000000000000000000000000..99b36913fae67d5d75178d2383e6430898d0509a
--- /dev/null
+++ b/src/mednet/libs/segmentation/tests/test_stare.py
@@ -0,0 +1,143 @@
+# SPDX-FileCopyrightText: Copyright © 2024 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+"""Tests for stare dataset."""
+
+import importlib
+
+import pytest
+from click.testing import CliRunner
+
+
+def id_function(val):
+    if isinstance(val, dict):
+        return str(val)
+    return repr(val)
+
+
+@pytest.mark.parametrize(
+    "split,lengths",
+    [
+        ("ah", dict(train=10, test=10)),
+        ("vk", dict(train=10, test=10)),
+    ],
+    ids=id_function,  # just changes how pytest prints it
+)
+def test_protocol_consistency(
+    database_checkers,
+    split: str,
+    lengths: dict[str, int],
+):
+    from mednet.libs.segmentation.config.data.stare.datamodule import (
+        make_split,
+    )
+
+    database_checkers.check_split(
+        make_split(f"{split}.json"),
+        lengths=lengths,
+    )
+
+
+@pytest.mark.skip_if_rc_var_not_set("datadir.stare")
+def test_database_check():
+    from mednet.libs.segmentation.scripts.database import check
+
+    runner = CliRunner()
+    result = runner.invoke(check, ["stare"])
+    assert (
+        result.exit_code == 0
+    ), f"Exit code {result.exit_code} != 0 -- Output:\n{result.output}"
+
+
+@pytest.mark.skip_if_rc_var_not_set("datadir.stare")
+@pytest.mark.parametrize(
+    "dataset",
+    [
+        "train",
+        "test",
+    ],
+)
+@pytest.mark.parametrize(
+    "name",
+    [
+        "ah",
+        "vk",
+    ],
+)
+def test_loading(database_checkers, name: str, dataset: str):
+    datamodule = importlib.import_module(
+        f".{name}",
+        "mednet.libs.segmentation.config.data.stare",
+    ).datamodule
+
+    datamodule.model_transforms = []  # should be done before setup()
+    datamodule.setup("predict")  # sets up all datasets
+
+    loader = datamodule.predict_dataloader()[dataset]
+
+    limit = 3  # limit load checking
+    for batch in loader:
+        if limit == 0:
+            break
+        database_checkers.check_loaded_batch(
+            batch,
+            batch_size=1,
+            color_planes=3,
+            expected_num_targets=1,
+        )
+        limit -= 1
+
+
+@pytest.mark.skip_if_rc_var_not_set("datadir.stare")
+def test_raw_transforms_image_quality(database_checkers, datadir):
+    reference_histogram_file = str(
+        datadir / "histograms/raw_data/histograms_stare_ah.json",
+    )
+
+    datamodule = importlib.import_module(
+        ".ah",
+        "mednet.libs.segmentation.config.data.stare",
+    ).datamodule
+
+    datamodule.model_transforms = []
+    datamodule.setup("predict")
+
+    database_checkers.check_image_quality(datamodule, reference_histogram_file)
+
+
+@pytest.mark.skip_if_rc_var_not_set("datadir.stare")
+@pytest.mark.parametrize(
+    "model_name",
+    ["lwnet"],
+)
+def test_model_transforms_image_quality(database_checkers, datadir, model_name):
+    # Densenet's model.name is "densenet-212" and does not correspond to its module name.
+    if model_name == "densenet":
+        reference_histogram_file = str(
+            datadir / "histograms/models/histograms_densenet-121_stare_ah.json",
+        )
+    else:
+        reference_histogram_file = str(
+            datadir
+            / f"histograms/models/histograms_{model_name}_stare_ah.json",
+        )
+
+    datamodule = importlib.import_module(
+        ".ah",
+        "mednet.libs.segmentation.config.data.stare",
+    ).datamodule
+
+    model = importlib.import_module(
+        f".{model_name}",
+        "mednet.libs.segmentation.config.models",
+    ).model
+
+    datamodule.model_transforms = model.model_transforms
+    datamodule.setup("predict")
+
+    database_checkers.check_image_quality(
+        datamodule,
+        reference_histogram_file,
+        compare_type="statistical",
+        pearson_coeff_threshold=0.005,
+    )