File size: 9,042 Bytes
d79c586
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
{
    "dataset_name": "Dataset001_Ink",
    "plans_name": "nnUNetPlans",
    "original_median_spacing_after_transp": [
        999.0,
        1.0,
        1.0
    ],
    "original_median_shape_after_transp": [
        1,
        1976,
        5280
    ],
    "image_reader_writer": "NaturalImage2DIO",
    "transpose_forward": [
        0,
        1,
        2
    ],
    "transpose_backward": [
        0,
        1,
        2
    ],
    "configurations": {
        "2d": {
            "data_identifier": "nnUNetPlans_2d",
            "preprocessor_name": "DefaultPreprocessor",
            "batch_size": 2,
            "patch_size": [
                768,
                2048
            ],
            "median_image_size_in_voxels": [
                1976.0,
                5280.0
            ],
            "spacing": [
                1.0,
                1.0
            ],
            "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": 9,
                    "features_per_stage": [
                        32,
                        64,
                        128,
                        256,
                        512,
                        512,
                        512,
                        512,
                        512
                    ],
                    "conv_op": "torch.nn.modules.conv.Conv2d",
                    "kernel_sizes": [
                        [
                            3,
                            3
                        ],
                        [
                            3,
                            3
                        ],
                        [
                            3,
                            3
                        ],
                        [
                            3,
                            3
                        ],
                        [
                            3,
                            3
                        ],
                        [
                            3,
                            3
                        ],
                        [
                            3,
                            3
                        ],
                        [
                            3,
                            3
                        ],
                        [
                            3,
                            3
                        ]
                    ],
                    "strides": [
                        [
                            1,
                            1
                        ],
                        [
                            2,
                            2
                        ],
                        [
                            2,
                            2
                        ],
                        [
                            2,
                            2
                        ],
                        [
                            2,
                            2
                        ],
                        [
                            2,
                            2
                        ],
                        [
                            2,
                            2
                        ],
                        [
                            2,
                            2
                        ],
                        [
                            1,
                            2
                        ]
                    ],
                    "n_conv_per_stage": [
                        2,
                        2,
                        2,
                        2,
                        2,
                        2,
                        2,
                        2,
                        2
                    ],
                    "n_conv_per_stage_decoder": [
                        2,
                        2,
                        2,
                        2,
                        2,
                        2,
                        2,
                        2
                    ],
                    "conv_bias": true,
                    "norm_op": "torch.nn.modules.instancenorm.InstanceNorm2d",
                    "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": true
        },
        "2d_rf128": {
            "inherits_from": "2d",
            "patch_size": [
                128,
                128
            ],
            "batch_size": 128,
            "architecture": {
                "network_class_name": "dynamic_network_architectures.architectures.unet.PlainConvUNet",
                "arch_kwargs": {
                    "n_stages": 4,
                    "features_per_stage": [
                        32,
                        64,
                        128,
                        256
                    ],
                    "conv_op": "torch.nn.modules.conv.Conv2d",
                    "kernel_sizes": [
                        [
                            3,
                            3
                        ],
                        [
                            3,
                            3
                        ],
                        [
                            3,
                            3
                        ],
                        [
                            3,
                            3
                        ]
                    ],
                    "strides": [
                        [
                            1,
                            1
                        ],
                        [
                            2,
                            2
                        ],
                        [
                            2,
                            2
                        ],
                        [
                            2,
                            2
                        ]
                    ],
                    "n_conv_per_stage": [
                        2,
                        2,
                        2,
                        2
                    ],
                    "n_conv_per_stage_decoder": [
                        2,
                        2,
                        2
                    ],
                    "conv_bias": true,
                    "norm_op": "torch.nn.modules.instancenorm.InstanceNorm2d",
                    "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"
                ]
            }
        }
    },
    "experiment_planner_used": "ExperimentPlanner",
    "label_manager": "LabelManager",
    "foreground_intensity_properties_per_channel": {
        "0": {
            "max": 255.0,
            "mean": 45.752685546875,
            "median": 4.0,
            "min": 0.0,
            "percentile_00_5": 0.0,
            "percentile_99_5": 255.0,
            "std": 84.74479675292969
        }
    }
}