adaptation_plan.json

{
    "architecture_plans": {
        "arch_class_name": "ResEncL",
        "arch_kwargs": null,
        "arch_kwargs_requiring_import": null
    },
    "pretrain_plan": {
        "dataset_name": "Dataset745_OpenNeuro_v2",
        "plans_name": "nnsslPlans",
        "original_median_spacing_after_transp": [
            1,
            1,
            1
        ],
        "image_reader_writer": "SimpleITKIO",
        "transpose_forward": [
            0,
            1,
            2
        ],
        "transpose_backward": [
            0,
            1,
            2
        ],
        "configurations": {
            "onemmiso": {
                "data_identifier": "nnsslPlans_3d_fullres",
                "preprocessor_name": "DefaultPreprocessor",
                "spacing_style": "onemmiso",
                "normalization_schemes": [
                    "ZScoreNormalization"
                ],
                "use_mask_for_norm": [
                    false
                ],
                "resampling_fn_data": "resample_data_or_seg_to_shape",
                "resampling_fn_data_kwargs": {
                    "is_seg": false,
                    "order": 3,
                    "order_z": 0,
                    "force_separate_z": null
                },
                "resampling_fn_mask": "resample_data_or_seg_to_shape",
                "resampling_fn_mask_kwargs": {
                    "is_seg": true,
                    "order": 1,
                    "order_z": 0,
                    "force_separate_z": null
                },
                "spacing": [
                    1,
                    1,
                    1
                ],
                "patch_size": [
                    64,
                    64,
                    64
                ]
            }
        },
        "experiment_planner_used": "FixedResEncUNetPlanner"
    },
    "pretrain_num_input_channels": 1,
    "recommended_downstream_patchsize": [
        160,
        160,
        160
    ],
    "key_to_encoder": "encoder.stages",
    "key_to_stem": "encoder.stem",
    "keys_to_in_proj": [
        "encoder.stem.convs.0.conv",
        "encoder.stem.convs.0.all_modules.0"
    ],
    "key_to_lpe": null,
    "citations": [
        {
            "type": "Architecture",
            "name": "ResEncL",
            "bibtex_citations": [
                "@inproceedings{isensee2024nnu,\n                title={nnu-net revisited: A call for rigorous validation in 3d medical image segmentation},\n                author={Isensee, Fabian and Wald, Tassilo and Ulrich, Constantin and Baumgartner, Michael and Roy, Saikat and Maier-Hein, Klaus and Jaeger, Paul F},\n                booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},\n                pages={488--498},\n                year={2024},\n                organization={Springer}\n                }"
            ]
        },
        {
            "type": "Pretraining Method",
            "name": "Masked Auto Encoder",
            "bibtex_citations": [
                "@article{wald2024revisiting,\n  title={Revisiting MAE pre-training for 3D medical image segmentation},\n  author={Wald, Tassilo and Ulrich, Constantin and Lukyanenko, Stanislav and Goncharov, Andrei and Paderno, Alberto and Maerkisch, Leander and J{\"a}ger, Paul F and Maier-Hein, Klaus},\n  journal={arXiv preprint arXiv:2410.23132},\n  year={2024}\n}"
            ]
        },
        {
            "type": "Pre-Training Dataset",
            "name": "OpenMind",
            "bibtex_citations": [
                "@article{wald2024openmind,\n    title={An OpenMind for 3D medical vision self-supervised learning},\n    author={Wald, Tassilo and Ulrich, Constantin and Suprijadi, Jonathan and Ziegler, Sebastian and Nohel, Michal and Peretzke, Robin and K{\"o}hler, Gregor and Maier-Hein, Klaus H},\n    journal={arXiv preprint arXiv:2412.17041},\n    year={2024}\n    }\n    "
            ]
        },
        {
            "type": "Framework",
            "name": "nnssl",
            "bibtex_citations": [
                "@article{wald2024revisiting,\n  title={Revisiting MAE pre-training for 3D medical image segmentation},\n  author={Wald, Tassilo and Ulrich, Constantin and Lukyanenko, Stanislav and Goncharov, Andrei and Paderno, Alberto and Maerkisch, Leander and J{\"a}ger, Paul F and Maier-Hein, Klaus},\n  journal={arXiv preprint arXiv:2410.23132},\n  year={2024}\n}"
            ]
        }
    ],
    "trainer_name": "BaseMAETrainer_BS8"
}