Project-MONAI · usmann56 · Sep 19, 2026 · Sep 19, 2026 · Sep 19, 2026
diff --git a/ci/bundle_custom_data.py b/ci/bundle_custom_data.py
@@ -53,6 +53,7 @@
     "cxr_image_synthesis_latent_diffusion_model",
     "brain_image_synthesis_latent_diffusion_model",
     "retinalOCT_RPD_segmentation",
+    "mindmap",
 ]
 
 # This list is used for our CI tests to determine whether a bundle needs to be tested after downloading

diff --git a/models/mindmap/LICENSE b/models/mindmap/LICENSE
@@ -0,0 +1,47 @@
+MIT License
+
+Copyright (c) 2024-2026 Sergey Plis and the neuroneural / brainchop-models contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+
+BSD 2-Clause License
+
+Copyright (c) 2020, Chris Rorden's Lab
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+1. Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+
+2. Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
diff --git a/models/mindmap/configs/inference.json b/models/mindmap/configs/inference.json
@@ -0,0 +1,102 @@
+{
+    "imports": [
+        "$import glob",
+        "$import numpy",
+        "$import os",
+        "$import scripts.checkpoint as checkpoint"
+    ],
+    "bundle_root": ".",
+    "image_key": "image",
+    "output_dir": "$@bundle_root + '/eval'",
+    "output_ext": ".nii.gz",
+    "output_dtype": "$numpy.uint8",
+    "output_postfix": "mindmap",
+    "separate_folder": true,
+    "load_pretrain": true,
+    "save_conform": false,
+    "dataset_dir": "/workspace/data/mindmap",
+    "datalist": "$list(sorted(glob.glob(@dataset_dir + '/*.nii') + glob.glob(@dataset_dir + '/*.nii.gz')))",
+    "device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')",
+    "network_def": {
+        "_target_": "scripts.network.MindMapNet"
+    },
+    "network": "$@network_def.to(@device)",
+    "preprocessing": {
+        "_target_": "Compose",
+        "transforms": [
+            {
+                "_target_": "LoadImaged",
+                "keys": "@image_key",
+                "ensure_channel_first": true,
+                "image_only": true
+            },
+            {
+                "_target_": "scripts.transforms.MindMapPreprocessd",
+                "keys": "@image_key"
+            },
+            {
+                "_target_": "EnsureTyped",
+                "keys": "@image_key",
+                "dtype": "$torch.float32"
+            }
+        ]
+    },
+    "dataset": {
+        "_target_": "Dataset",
+        "data": "$[{'image': i} for i in @datalist]",
+        "transform": "@preprocessing"
+    },
+    "dataloader": {
+        "_target_": "DataLoader",
+        "dataset": "@dataset",
+        "batch_size": 1,
+        "shuffle": false,
+        "num_workers": 0
+    },
+    "inferer": {
+        "_target_": "SimpleInferer"
+    },
+    "postprocessing": {
+        "_target_": "Compose",
+        "transforms": [
+            {
+                "_target_": "scripts.transforms.MindMapPostprocessd",
+                "keys": "pred",
+                "save_conform": "@save_conform"
+            },
+            {
+                "_target_": "SaveImaged",
+                "keys": "pred",
+                "output_dir": "@output_dir",
+                "output_ext": "@output_ext",
+                "output_dtype": "@output_dtype",
+                "output_postfix": "@output_postfix",
+                "separate_folder": "@separate_folder"
+            }
+        ]
+    },
+    "handlers": [
+        {
+            "_target_": "StatsHandler",
+            "iteration_log": false
+        }
+    ],
+    "evaluator": {
+        "_target_": "SupervisedEvaluator",
+        "device": "@device",
+        "val_data_loader": "@dataloader",
+        "network": "@network",
+        "inferer": "@inferer",
+        "postprocessing": "@postprocessing",
+        "val_handlers": "@handlers",
+        "amp": false
+    },
+    "checkpoint_sha256": "b87a1646ef21848f4df17c63e3f1ab1087e50d4e859d2e4ab0da9677d234f80e",
+    "initialize": [
+        "$monai.utils.set_determinism(seed=123)",
+        "$checkpoint.load_meshnet_gn_checkpoint(@network, @bundle_root + '/models/model.pt', @checkpoint_sha256) if @load_pretrain else None"
+    ],
+    "run": [
+        "$@evaluator.run()"
+    ]
+}
diff --git a/models/mindmap/configs/metadata.json b/models/mindmap/configs/metadata.json
@@ -0,0 +1,95 @@
+{
+    "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json",
+    "version": "0.1.0",
+    "changelog": {
+        "0.1.0": "initialize the model package structure"
+    },
+    "monai_version": "1.6.0",
+    "pytorch_version": "2.14.0",
+    "numpy_version": "2.4.0",
+    "required_packages_version": {
+        "nibabel": "5.4.2",
+        "scipy": "1.18.1",
+        "pytorch-ignite": "0.5.2",
+        "safetensors": "0.8.0"
+    },
+    "supported_apps": {},
+    "name": "MindMap Brain Segmentation",
+    "task": "18-class whole-brain segmentation (gray/white matter and subcortical structures) in any imaging modality",
+    "description": "A 24-channel, 13-layer dilated 3D CNN (MeshNet-style; this is model24chan18cls, which shares model16chan18cls's exact topology at 24 instead of 16 channels) that segments a 3D medical image into 18 FreeSurfer-style brain regions, ported from the mindmap model (published as model24chan18cls_gdice_prio in neuroneural/brainchop-test) so it runs as a standard MONAI bundle. The bundle reproduces the upstream reference implementation's full inference pipeline: intensity-clip and reslice the input onto a 256x256x256, 1mm, LIA-oriented conform grid, quantile-normalize it, run the network, keep only the single largest 26-connected foreground component (across all classes jointly), and reslice the label map back onto the input's native grid.",
+    "authors": "Sergey Plis and the neuroneural / brainchop-models team (original model16chan18cls/model24chan18cls training); ported to MONAI bundle format by the MONAI Model Zoo community",
+    "copyright": "Copyright (c) MONAI Consortium",
+    "data_source": "Trained on SynthSeg-style synthetic data (synth18 / label18); not otherwise documented by this port. See the upstream brainchop-models project for the original training details.",
+    "data_type": "nibabel",
+    "image_classes": "single channel data, any modality, any input size/orientation (internally resampled to a 256x256x256, 1mm conform grid)",
+    "label_classes": "18 FreeSurfer-style whole-brain classes: Unknown/background, Cerebral-White-Matter, Cerebral-Cortex, Lateral-Ventricle, Inferior-Lateral-Ventricle, Cerebellum-White-Matter, Cerebellum-Cortex, Thalamus, Caudate, Putamen, Pallidum, 3rd-Ventricle, 4th-Ventricle, Brain-Stem, Hippocampus, Amygdala, Accumbens-area, VentralDC",
+    "pred_classes": "18 channels, conform-space network logits (channel 0 is background/Unknown), before this bundle's postprocessing argmaxes, cleans up, and reslices them into a single-channel label map",
+    "eval_metrics": {},
+    "intended_use": "This is an example, not to be used for diagnostic purposes",
+    "references": [
+        "brainchop-models, the upstream training/checkpoint repository this bundle's weights are pulled from: https://github.com/neuroneural/brainchop-models/tree/f53f7b93d725416c2705a9e4f79765d1739badb9/meshnet/model24chan18cls",
+        "neuroneural/brainchop-test, which publishes this model's weights/config publicly as model24chan18cls_gdice_prio: https://github.com/neuroneural/brainchop-test/tree/webgpu/public/models/model24chan18cls_gdice_prio"
+    ],
+    "network_data_format": {
+        "inputs": {
+            "image": {
+                "type": "image",
+                "format": "any modality",
+                "modality": "any",
+                "num_channels": 1,
+                "spatial_shape": [
+                    256,
+                    256,
+                    256
+                ],
+                "dtype": "float32",
+                "value_range": [
+                    -1,
+                    2
+                ],
+                "is_patch_data": false,
+                "channel_def": {
+                    "0": "image"
+                }
+            }
+        },
+        "outputs": {
+            "pred": {
+                "type": "image",
+                "format": "segmentation",
+                "num_channels": 18,
+                "spatial_shape": [
+                    256,
+                    256,
+                    256
+                ],
+                "dtype": "float32",
+                "value_range": [
+                    -100,
+                    100
+                ],
+                "is_patch_data": false,
+                "channel_def": {
+                    "0": "Unknown",
+                    "1": "Cerebral-White-Matter",
+                    "2": "Cerebral-Cortex",
+                    "3": "Lateral-Ventricle",
+                    "4": "Inferior-Lateral-Ventricle",
+                    "5": "Cerebellum-White-Matter",
+                    "6": "Cerebellum-Cortex",
+                    "7": "Thalamus",
+                    "8": "Caudate",
+                    "9": "Putamen",
+                    "10": "Pallidum",
+                    "11": "3rd-Ventricle",
+                    "12": "4th-Ventricle",
+                    "13": "Brain-Stem",
+                    "14": "Hippocampus",
+                    "15": "Amygdala",
+                    "16": "Accumbens-area",
+                    "17": "VentralDC"
+                }
+            }
+        }
+    }
+}