{
    "dataset_name": "Dataset225_nnInteractiveV2",
    "plans_name": "nnUNetResEncUNetLPlans_noResampling",
    "original_median_spacing_after_transp": [
        1.25,
        1.0,
        1.0
    ],
    "original_median_shape_after_transp": [
        139,
        248,
        250
    ],
    "image_reader_writer": "NibabelIOWithReorient",
    "transpose_forward": [
        0,
        1,
        2
    ],
    "transpose_backward": [
        0,
        1,
        2
    ],
    "configurations": {
        "3d_fullres_ps192": {
            "data_identifier": "nnUNetResEncUNetLPlans_noResampling_3d_fullres",
            "preprocessor_name": "DefaultPreprocessor",
            "batch_size": 2,
            "patch_size": [
                192,
                192,
                192
            ],
            "median_image_size_in_voxels": [
                168.0,
                239.0,
                282.0
            ],
            "spacing": [
                1.5,
                1.5,
                1.5
            ],
            "normalization_schemes": [
                "ZScoreNormalization"
            ],
            "use_mask_for_norm": [
                false
            ],
            "resampling_fn_data": "no_resampling_hack",
            "resampling_fn_seg": "no_resampling_hack",
            "resampling_fn_data_kwargs": {},
            "resampling_fn_seg_kwargs": {},
            "resampling_fn_probabilities": "no_resampling_hack",
            "resampling_fn_probabilities_kwargs": {},
            "architecture": {
                "network_class_name": "dynamic_network_architectures.architectures.unet.ResidualEncoderUNet",
                "arch_kwargs": {
                    "n_stages": 6,
                    "features_per_stage": [
                        32,
                        64,
                        128,
                        256,
                        320,
                        320
                    ],
                    "conv_op": "torch.nn.modules.conv.Conv3d",
                    "kernel_sizes": [
                        [
                            3,
                            3,
                            3
                        ],
                        [
                            3,
                            3,
                            3
                        ],
                        [
                            3,
                            3,
                            3
                        ],
                        [
                            3,
                            3,
                            3
                        ],
                        [
                            3,
                            3,
                            3
                        ],
                        [
                            3,
                            3,
                            3
                        ]
                    ],
                    "strides": [
                        [
                            1,
                            1,
                            1
                        ],
                        [
                            2,
                            2,
                            2
                        ],
                        [
                            2,
                            2,
                            2
                        ],
                        [
                            2,
                            2,
                            2
                        ],
                        [
                            2,
                            2,
                            2
                        ],
                        [
                            2,
                            2,
                            2
                        ]
                    ],
                    "n_blocks_per_stage": [
                        1,
                        3,
                        4,
                        6,
                        6,
                        6
                    ],
                    "n_conv_per_stage_decoder": [
                        1,
                        1,
                        1,
                        1,
                        1
                    ],
                    "conv_bias": true,
                    "norm_op": "torch.nn.modules.instancenorm.InstanceNorm3d",
                    "norm_op_kwargs": {
                        "eps": 1e-05,
                        "affine": true
                    },
                    "dropout_op": null,
                    "dropout_op_kwargs": null,
                    "nonlin": "torch.nn.LeakyReLU",
                    "nonlin_kwargs": {
                        "inplace": true
                    }
                },
                "_kw_requires_import": [
                    "conv_op",
                    "norm_op",
                    "dropout_op",
                    "nonlin"
                ]
            },
            "batch_dice": false
        },
        "3d_fullres_ps192_bs16": {
            "inherits_from": "3d_fullres_ps192",
            "batch_size": 16
        },
        "3d_fullres_ps192_bs24": {
            "inherits_from": "3d_fullres_ps192",
            "batch_size": 24
        },
        "3d_fullres_ps192_bs2": {
            "inherits_from": "3d_fullres_ps192_bs16",
            "batch_size": 2
        },
        "3d_fullres_ps128_bs2": {
            "inherits_from": "3d_fullres_ps192_bs2",
            "patch_size": [
                128,
                128,
                128
            ]
        },
        "3d_fullres_ps384_bs16": {
            "inherits_from": "3d_fullres_ps192_bs16",
            "patch_size": [
                384,
                384,
                384
            ]
        }
    },
    "experiment_planner_used": "nnUNetPlannerResEncL_noResampling",
    "label_manager": "LabelManager",
    "foreground_intensity_properties_per_channel": {
        "0": {
            "max": 4094640.0,
            "mean": 1683.86181640625,
            "median": 374.0,
            "min": -32768.0,
            "percentile_00_5": -970.0,
            "percentile_99_5": 8047.0,
            "std": 26629.310546875
        }
    }
}