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baselines/AMAES_original_README.md

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+---
+license: cc-by-nc-sa-4.0
+datasets:
+- FOMO-MRI/FOMO300K
+pipeline_tag: image-segmentation
+---
+
+# ResEnc UNet pretrained on FOMO300K using AMAES
+
+This repository contains the checkpoint of the model from the [FOMO300K paper](https://arxiv.org/abs/2506.14432).
+
+NB: This checkpoint was trained on an earlier version of FOMO300K, which included 11K scans that are no longer part of the dataset.
+
+* Network: Resenc Unet B with 102M parameters ([model definition](https://github.com/Sllambias/asparagus/blob/72f333b9b59cf9c2a5689995b72a06d689707fec/asparagus/modules/networks/resenc_unet.py#L119))
+* Pretext Task: [AMAES](https://arxiv.org/abs/2408.00640).
+* Dataset: [FOMO300K](https://huggingface.co/datasets/FOMO-MRI/FOMO300K).
+* Code: [Asparagus](https://github.com/Sllambias/asparagus). 
+
+## Finetuning the model for Segmentation tasks
+
+To finetune the model with the configs used in the paper, simply use the following command
+```
+asp_finetune_seg \
+    --config-name projects/datapaper/finetune/resenc_[dataset]_fewshot.yaml \
+    checkpoint_path=path/to/checkpoint.ckpt
+```
+where `[dataset]` is one of `{cerebrum, wmh, isles, atlas, sbm}`.
+
+
+## Installing Asparagus
+
+For instructions on how to install asparagus, preprocess your data, and make your own configs, please refer to the [Asparagus Readme](https://github.com/Sllambias/asparagus).

baselines/resenc_unet_b.ckpt

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baselines/resenc_unet_b_5ch.ckpt

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