diff --git a/pyproject.toml b/pyproject.toml
index 0be3495ef1bda54fe004d446c5d2f0b47fdc0591..2ec302d69d3f0bacbefa13d19ac905f022e6a617 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -423,8 +423,14 @@ visceral = "mednet.config.data.visceral.default"
 
 lwnet = "mednet.libs.segmentation.config.models.lwnet"
 
-# drive dataset - retinal vessel segmentation
+# chase-db1 - retinography
+chasedb1 = "mednet.libs.segmentation.config.data.chasedb1.first_annotator"
+chasedb1-2nd = "mednet.libs.segmentation.config.data.chasedb1.second_annotator"
+
+# drive dataset - retinography
 drive = "mednet.libs.segmentation.config.data.drive.default"
+
+# stare dataset - retinography
 stare = "mednet.libs.segmentation.config.data.stare.ah"
 stare-2nd = "mednet.libs.segmentation.config.data.stare.vk"
 
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/__init__.py b/src/mednet/libs/segmentation/config/data/chasedb1/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/datamodule.py b/src/mednet/libs/segmentation/config/data/chasedb1/datamodule.py
new file mode 100644
index 0000000000000000000000000000000000000000..f8dfa0bc895d49e77f4191259b7ef4d67f8a2e8b
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/chasedb1/datamodule.py
@@ -0,0 +1,135 @@
+# SPDX-FileCopyrightText: Copyright © 2024 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+"""CHASE-DB1 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 Chase-db1 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 path suffixes to the sample image, target, and mask
+            to be loaded, within the dataset root folder.
+
+        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 Chase-db1 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):
+    """CHASE-DB1 dataset for Vessel Segmentation.
+
+    The CHASE_DB1 is a retinal vessel reference dataset acquired from multiethnic
+    school children. This database is a part of the Child Heart and Health Study in
+    England (CHASE), a cardiovascular health survey in 200 primary schools in
+    London, Birmingham, and Leicester. The ocular imaging was carried out in
+    46 schools and demonstrated associations between retinal vessel tortuosity and
+    early risk factors for cardiovascular disease in over 1000 British primary
+    school children of different ethnic origin. The retinal images of both of the
+    eyes of each child were recorded with a hand-held Nidek NM-200-D fundus camera.
+    The images were captured at 30 degrees FOV camera. The dataset of images are
+    characterized by having nonuniform back-ground illumination, poor contrast of
+    blood vessels as compared with the background and wider arteriolars that have a
+    bright strip running down the centre known as the central vessel reflex.
+
+    * Reference: [CHASEDB1-2012]_
+    * Original resolution (height x width): 960 x 999
+    * Split reference: [CHASEDB1-2012]_
+    * Protocol ``first-annotator``:
+
+    * Training samples: 8 (including labels from annotator "1stHO")
+    * Test samples: 20 (including labels from annotator "1stHO")
+
+    * Protocol ``second-annotator``:
+
+    * Training samples: 8 (including labels from annotator "2ndHO")
+    * Test samples: 20 (including labels from annotator "2ndHO")
+
+    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/chasedb1/first-annotator.json b/src/mednet/libs/segmentation/config/data/chasedb1/first-annotator.json
new file mode 100644
index 0000000000000000000000000000000000000000..5233507747e93d3d273a0f725c33e793e88fd540
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/chasedb1/first-annotator.json
@@ -0,0 +1,146 @@
+{
+ "train": [
+  [
+   "Image_11L.jpg",
+   "Image_11L_1stHO.png",
+   "Image_11L.png"
+  ],
+  [
+   "Image_11R.jpg",
+   "Image_11R_1stHO.png",
+   "Image_11R.png"
+  ],
+  [
+   "Image_12L.jpg",
+   "Image_12L_1stHO.png",
+   "Image_12L.png"
+  ],
+  [
+   "Image_12R.jpg",
+   "Image_12R_1stHO.png",
+   "Image_12R.png"
+  ],
+  [
+   "Image_13L.jpg",
+   "Image_13L_1stHO.png",
+   "Image_13L.png"
+  ],
+  [
+   "Image_13R.jpg",
+   "Image_13R_1stHO.png",
+   "Image_13R.png"
+  ],
+  [
+   "Image_14L.jpg",
+   "Image_14L_1stHO.png",
+   "Image_14L.png"
+  ],
+  [
+   "Image_14R.jpg",
+   "Image_14R_1stHO.png",
+   "Image_14R.png"
+  ]
+ ],
+ "test": [
+  [
+   "Image_01L.jpg",
+   "Image_01L_1stHO.png",
+   "Image_01L.png"
+  ],
+  [
+   "Image_01R.jpg",
+   "Image_01R_1stHO.png",
+   "Image_01R.png"
+  ],
+  [
+   "Image_02L.jpg",
+   "Image_02L_1stHO.png",
+   "Image_02L.png"
+  ],
+  [
+   "Image_02R.jpg",
+   "Image_02R_1stHO.png",
+   "Image_02R.png"
+  ],
+  [
+   "Image_03L.jpg",
+   "Image_03L_1stHO.png",
+   "Image_03L.png"
+  ],
+  [
+   "Image_03R.jpg",
+   "Image_03R_1stHO.png",
+   "Image_03R.png"
+  ],
+  [
+   "Image_04L.jpg",
+   "Image_04L_1stHO.png",
+   "Image_04L.png"
+  ],
+  [
+   "Image_04R.jpg",
+   "Image_04R_1stHO.png",
+   "Image_04R.png"
+  ],
+  [
+   "Image_05L.jpg",
+   "Image_05L_1stHO.png",
+   "Image_05L.png"
+  ],
+  [
+   "Image_05R.jpg",
+   "Image_05R_1stHO.png",
+   "Image_05R.png"
+  ],
+  [
+   "Image_06L.jpg",
+   "Image_06L_1stHO.png",
+   "Image_06L.png"
+  ],
+  [
+   "Image_06R.jpg",
+   "Image_06R_1stHO.png",
+   "Image_06R.png"
+  ],
+  [
+   "Image_07L.jpg",
+   "Image_07L_1stHO.png",
+   "Image_07L.png"
+  ],
+  [
+   "Image_07R.jpg",
+   "Image_07R_1stHO.png",
+   "Image_07R.png"
+  ],
+  [
+   "Image_08L.jpg",
+   "Image_08L_1stHO.png",
+   "Image_08L.png"
+  ],
+  [
+   "Image_08R.jpg",
+   "Image_08R_1stHO.png",
+   "Image_08R.png"
+  ],
+  [
+   "Image_09L.jpg",
+   "Image_09L_1stHO.png",
+   "Image_09L.png"
+  ],
+  [
+   "Image_09R.jpg",
+   "Image_09R_1stHO.png",
+   "Image_09R.png"
+  ],
+  [
+   "Image_10L.jpg",
+   "Image_10L_1stHO.png",
+   "Image_10L.png"
+  ],
+  [
+   "Image_10R.jpg",
+   "Image_10R_1stHO.png",
+   "Image_10R.png"
+  ]
+ ]
+}
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/first_annotator.py b/src/mednet/libs/segmentation/config/data/chasedb1/first_annotator.py
new file mode 100644
index 0000000000000000000000000000000000000000..eae56453c605b6c4203a54a4625e81d8568d1210
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/chasedb1/first_annotator.py
@@ -0,0 +1,8 @@
+# SPDX-FileCopyrightText: Copyright © 2024 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+"""CHASE-DB1 dataset for Vessel Segmentation."""
+
+from mednet.libs.segmentation.config.data.chasedb1.datamodule import DataModule
+
+datamodule = DataModule("first-annotator.json")
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_01L.png b/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_01L.png
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diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/second-annotator.json b/src/mednet/libs/segmentation/config/data/chasedb1/second-annotator.json
new file mode 100644
index 0000000000000000000000000000000000000000..9f2da7f2749462e0a941b8ab89e503c618530b09
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/chasedb1/second-annotator.json
@@ -0,0 +1,146 @@
+{
+ "train": [
+  [
+   "Image_11L.jpg",
+   "Image_11L_2ndHO.png",
+   "Image_11L.png"
+  ],
+  [
+   "Image_11R.jpg",
+   "Image_11R_2ndHO.png",
+   "Image_11R.png"
+  ],
+  [
+   "Image_12L.jpg",
+   "Image_12L_2ndHO.png",
+   "Image_12L.png"
+  ],
+  [
+   "Image_12R.jpg",
+   "Image_12R_2ndHO.png",
+   "Image_12R.png"
+  ],
+  [
+   "Image_13L.jpg",
+   "Image_13L_2ndHO.png",
+   "Image_13L.png"
+  ],
+  [
+   "Image_13R.jpg",
+   "Image_13R_2ndHO.png",
+   "Image_13R.png"
+  ],
+  [
+   "Image_14L.jpg",
+   "Image_14L_2ndHO.png",
+   "Image_14L.png"
+  ],
+  [
+   "Image_14R.jpg",
+   "Image_14R_2ndHO.png",
+   "Image_14R.png"
+  ]
+ ],
+ "test": [
+  [
+   "Image_01L.jpg",
+   "Image_01L_2ndHO.png",
+   "Image_01L.png"
+  ],
+  [
+   "Image_01R.jpg",
+   "Image_01R_2ndHO.png",
+   "Image_01R.png"
+  ],
+  [
+   "Image_02L.jpg",
+   "Image_02L_2ndHO.png",
+   "Image_02L.png"
+  ],
+  [
+   "Image_02R.jpg",
+   "Image_02R_2ndHO.png",
+   "Image_02R.png"
+  ],
+  [
+   "Image_03L.jpg",
+   "Image_03L_2ndHO.png",
+   "Image_03L.png"
+  ],
+  [
+   "Image_03R.jpg",
+   "Image_03R_2ndHO.png",
+   "Image_03R.png"
+  ],
+  [
+   "Image_04L.jpg",
+   "Image_04L_2ndHO.png",
+   "Image_04L.png"
+  ],
+  [
+   "Image_04R.jpg",
+   "Image_04R_2ndHO.png",
+   "Image_04R.png"
+  ],
+  [
+   "Image_05L.jpg",
+   "Image_05L_2ndHO.png",
+   "Image_05L.png"
+  ],
+  [
+   "Image_05R.jpg",
+   "Image_05R_2ndHO.png",
+   "Image_05R.png"
+  ],
+  [
+   "Image_06L.jpg",
+   "Image_06L_2ndHO.png",
+   "Image_06L.png"
+  ],
+  [
+   "Image_06R.jpg",
+   "Image_06R_2ndHO.png",
+   "Image_06R.png"
+  ],
+  [
+   "Image_07L.jpg",
+   "Image_07L_2ndHO.png",
+   "Image_07L.png"
+  ],
+  [
+   "Image_07R.jpg",
+   "Image_07R_2ndHO.png",
+   "Image_07R.png"
+  ],
+  [
+   "Image_08L.jpg",
+   "Image_08L_2ndHO.png",
+   "Image_08L.png"
+  ],
+  [
+   "Image_08R.jpg",
+   "Image_08R_2ndHO.png",
+   "Image_08R.png"
+  ],
+  [
+   "Image_09L.jpg",
+   "Image_09L_2ndHO.png",
+   "Image_09L.png"
+  ],
+  [
+   "Image_09R.jpg",
+   "Image_09R_2ndHO.png",
+   "Image_09R.png"
+  ],
+  [
+   "Image_10L.jpg",
+   "Image_10L_2ndHO.png",
+   "Image_10L.png"
+  ],
+  [
+   "Image_10R.jpg",
+   "Image_10R_2ndHO.png",
+   "Image_10R.png"
+  ]
+ ]
+}
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/second_annotator.py b/src/mednet/libs/segmentation/config/data/chasedb1/second_annotator.py
new file mode 100644
index 0000000000000000000000000000000000000000..90c02cffa37f293df88532a60d6dbfe071683918
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/chasedb1/second_annotator.py
@@ -0,0 +1,8 @@
+# SPDX-FileCopyrightText: Copyright © 2024 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+"""CHASE-DB1 dataset for Vessel Segmentation."""
+
+from mednet.libs.segmentation.config.data.chasedb1.datamodule import DataModule
+
+datamodule = DataModule("second-annotator.json")
diff --git a/src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_chasedb1_first_annotator.json b/src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_chasedb1_first_annotator.json
new file mode 100644
index 0000000000000000000000000000000000000000..ec8254dea59b08026659e9d95ca38e3b5cb65f96
--- /dev/null
+++ b/src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_chasedb1_first_annotator.json
@@ -0,0 +1,16 @@
+{
+  "train": [
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+}
diff --git a/src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_chasedb1_first_annotator.json b/src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_chasedb1_first_annotator.json
new file mode 100644
index 0000000000000000000000000000000000000000..ab664159fad42eaf3975e49d1cc676e01db66454
--- /dev/null
+++ b/src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_chasedb1_first_annotator.json
@@ -0,0 +1,16 @@
+{
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+    ["Image_10L.jpg", [281397, 4462, 573, 2112, 1231, 346, 745, 673, 606, 200, 449, 396, 152, 341, 310, 278, 152, 182, 184, 162, 164, 117, 144, 108, 124, 110, 116, 105, 108, 123, 97, 108, 108, 86, 91, 74, 93, 83, 99, 71, 102, 71, 86, 74, 77, 80, 102, 90, 98, 121, 132, 139, 186, 285, 338, 482, 534, 545, 646, 523, 494, 512, 443, 511, 627, 722, 841, 925, 961, 1034, 1112, 1149, 1354, 1249, 1254, 1368, 1392, 1443, 1608, 1867, 2090, 2145, 2101, 2168, 2068, 1929, 1893, 1941, 2082, 2081, 2085, 2261, 2323, 2649, 3033, 3362, 3799, 4374, 4628, 5373, 6130, 6755, 7336, 7654, 7709, 8338, 8670, 8957, 9474, 10078, 10630, 10617, 10880, 10872, 10503, 10424, 10131, 10370, 9788, 9614, 9729, 9739, 9493, 9477, 8977, 8814, 8468, 8060, 7718, 7609, 7167, 7017, 6933, 6767, 6595, 6428, 6306, 6144, 6131, 5673, 5502, 5411, 5264, 4857, 4849, 4751, 4585, 4355, 4298, 4194, 4076, 4092, 3834, 3802, 3691, 3643, 3556, 3479, 3526, 3457, 3470, 3418, 3488, 3379, 3406, 3375, 3350, 3296, 3204, 3094, 3030, 2980, 2812, 2776, 2691, 2584, 2334, 2360, 2265, 2143, 2059, 1955, 1922, 1839, 1888, 1798, 1751, 1717, 1695, 1627, 1573, 1617, 1482, 1474, 1479, 1364, 1342, 1295, 1285, 1222, 1260, 1184, 1177, 1103, 1149, 1136, 1068, 1066, 1068, 1023, 1036, 981, 935, 993, 889, 902, 888, 865, 878, 819, 713, 775, 688, 698, 706, 685, 636, 618, 618, 577, 523, 548, 495, 512, 477, 478, 455, 401, 412, 401, 409, 440, 424, 451, 478, 543, 631, 740, 943, 1195, 1480, 1834, 2094, 2644, 3196, 17424, 286491, 5522, 2046, 973, 624, 313, 203, 167, 175, 137, 145, 110, 123, 126, 108, 126, 127, 122, 146, 99, 113, 126, 131, 179, 282, 435, 693, 890, 1002, 1122, 1273, 1619, 2282, 2823, 3500, 3940, 4117, 4718, 5528, 5989, 6631, 6626, 6998, 7885, 9336, 11360, 12974, 13970, 14822, 16577, 19194, 21083, 22050, 21811, 20882, 19634, 19317, 19375, 19188, 18533, 17296, 15853, 14888, 14320, 13168, 11621, 10623, 9503, 9263, 8651, 7993, 7415, 6561, 5805, 5630, 5260, 5037, 4920, 4669, 4645, 4433, 4427, 4244, 4286, 4028, 3752, 3695, 3561, 3562, 3408, 3288, 3053, 2980, 2759, 2734, 2638, 2510, 2333, 2255, 2208, 2197, 2019, 2013, 1984, 1863, 1839, 1762, 1750, 1704, 1653, 1512, 1572, 1478, 1297, 1340, 1246, 1257, 1182, 1069, 1051, 976, 928, 882, 862, 830, 814, 747, 744, 776, 711, 699, 618, 660, 553, 557, 553, 591, 537, 513, 486, 454, 508, 446, 434, 416, 423, 392, 374, 346, 352, 318, 309, 275, 259, 250, 204, 249, 206, 200, 171, 181, 148, 168, 166, 133, 155, 150, 140, 122, 153, 103, 140, 121, 101, 119, 121, 105, 108, 108, 92, 91, 87, 93, 79, 84, 104, 92, 77, 89, 78, 96, 93, 90, 78, 69, 68, 92, 74, 70, 93, 83, 79, 69, 58, 66, 62, 81, 67, 49, 79, 67, 67, 57, 65, 71, 56, 52, 51, 62, 50, 47, 48, 43, 37, 42, 39, 31, 43, 57, 43, 41, 41, 36, 42, 34, 34, 38, 38, 30, 34, 40, 27, 30, 40, 40, 36, 29, 30, 50, 44, 66, 91, 105, 246, 659, 2510, 286962, 2178, 6925, 5068, 9483, 11557, 14074, 18131, 21722, 26003, 29482, 33109, 35892, 37206, 37030, 35034, 32812, 30039, 27476, 25033, 22714, 21022, 19497, 17957, 16689, 15585, 14262, 13021, 11124, 9637, 7867, 6612, 5492, 4850, 4206, 3723, 3416, 3150, 2910, 2697, 2425, 2190, 1923, 1719, 1475, 1289, 1167, 1010, 961, 876, 766, 702, 596, 629, 574, 513, 424, 406, 376, 357, 321, 326, 240, 268, 238, 220, 185, 187, 184, 159, 141, 107, 104, 94, 105, 104, 120, 131, 121, 143, 145, 112, 118, 94, 169, 167, 73, 132, 65, 141, 106, 151, 180, 124, 103, 123, 69, 107, 52, 114, 85, 105, 101, 81, 39, 60, 30, 43, 34, 25, 77, 69, 32, 86, 19, 90, 21, 75, 23, 22, 25, 21, 0, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]
+  ]
+}
diff --git a/src/mednet/libs/segmentation/tests/test_chasedb1.py b/src/mednet/libs/segmentation/tests/test_chasedb1.py
new file mode 100644
index 0000000000000000000000000000000000000000..145bb4dbafeb5aea50e67211f6f2a3a7607c3279
--- /dev/null
+++ b/src/mednet/libs/segmentation/tests/test_chasedb1.py
@@ -0,0 +1,138 @@
+# SPDX-FileCopyrightText: Copyright © 2024 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+"""Tests for chasedb1 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",
+    [
+        ("first-annotator", dict(train=8, test=20)),
+        ("second-annotator", dict(train=8, test=20)),
+    ],
+    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.chasedb1.datamodule import (
+        make_split,
+    )
+
+    database_checkers.check_split(
+        make_split(f"{split}.json"),
+        lengths=lengths,
+    )
+
+
+@pytest.mark.skip_if_rc_var_not_set("datadir.chasedb1")
+def test_database_check():
+    from mednet.libs.segmentation.scripts.database import check
+
+    runner = CliRunner()
+    result = runner.invoke(check, ["chasedb1"])
+    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.chasedb1")
+@pytest.mark.parametrize(
+    "dataset",
+    [
+        "train",
+        "test",
+    ],
+)
+@pytest.mark.parametrize(
+    "name",
+    [
+        "first_annotator",
+        "second_annotator",
+    ],
+)
+def test_loading(database_checkers, name: str, dataset: str):
+    datamodule = importlib.import_module(
+        f".{name}",
+        "mednet.libs.segmentation.config.data.chasedb1",
+    ).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.chasedb1")
+def test_raw_transforms_image_quality(database_checkers, datadir):
+    reference_histogram_file = str(
+        datadir
+        / "histograms/raw_data/histograms_chasedb1_first_annotator.json",
+    )
+
+    datamodule = importlib.import_module(
+        ".first_annotator",
+        "mednet.libs.segmentation.config.data.chasedb1",
+    ).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.chasedb1")
+@pytest.mark.parametrize(
+    "model_name",
+    ["lwnet"],
+)
+def test_model_transforms_image_quality(database_checkers, datadir, model_name):
+    reference_histogram_file = str(
+        datadir
+        / f"histograms/models/histograms_{model_name}_chasedb1_first_annotator.json",
+    )
+
+    datamodule = importlib.import_module(
+        ".first_annotator",
+        "mednet.libs.segmentation.config.data.chasedb1",
+    ).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,
+    )