plans.json

{
    "dataset_name": "Dataset203_BreastDivider",
    "plans_name": "nnUNetPlans",
    "original_median_spacing_after_transp": [
        1.9861830472946167,
        0.7031000256538391,
        0.7031000256538391
    ],
    "original_median_shape_after_transp": [
        116,
        489,
        510
    ],
    "image_reader_writer": "SimpleITKIOWithReorient",
    "transpose_forward": [
        0,
        1,
        2
    ],
    "transpose_backward": [
        0,
        1,
        2
    ],
    "configurations": {
        "3d_dac": {
            "data_identifier": "nnUNetPlans_3d_dac",
            "preprocessor_name": "DefaultPreprocessor",
            "batch_size": 3,
            "patch_size": [
                128,
                128,
                128
            ],
            "median_image_size_in_voxels": [
                106.0,
                477.0,
                484.0
            ],
            "spacing": [
                1.6448078360408545,
                2.620146189350635,
                2.658596972003579
            ],
            "normalization_schemes": [
                "ZScoreNormalization"
            ],
            "use_mask_for_norm": [
                false
            ],
            "resampling_fn_data": "resample_data_or_seg_to_shape",
            "resampling_fn_seg": "resample_data_or_seg_to_shape",
            "resampling_fn_data_kwargs": {
                "is_seg": false,
                "order": 3,
                "order_z": 0,
                "force_separate_z": null
            },
            "resampling_fn_seg_kwargs": {
                "is_seg": true,
                "order": 1,
                "order_z": 0,
                "force_separate_z": null
            },
            "resampling_fn_probabilities": "resample_data_or_seg_to_shape",
            "resampling_fn_probabilities_kwargs": {
                "is_seg": false,
                "order": 1,
                "order_z": 0,
                "force_separate_z": null
            },
            "architecture": {
                "network_class_name": "dynamic_network_architectures.architectures.unet.PlainConvUNet",
                "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_conv_per_stage": [
                        2,
                        2,
                        2,
                        2,
                        2,
                        2
                    ],
                    "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
        }
    },
    "experiment_planner_used": "ExperimentPlanner",
    "label_manager": "LabelManager",
    "foreground_intensity_properties_per_channel": {
        "0": {
            "max": 32760.0,
            "mean": 341.6798400878906,
            "median": 139.00372314453125,
            "min": -737.0,
            "percentile_00_5": 0.0,
            "percentile_99_5": 3482.0,
            "std": 559.0700073242188
        }
    }
}