diff --git a/mice_uqueensland_sc.json b/mice_uqueensland_sc.json index e036b08..a7929a4 100644 --- a/mice_uqueensland_sc.json +++ b/mice_uqueensland_sc.json @@ -1,87 +1,105 @@ { "command": "train", - "gpu": 5, - "target_suffix": "_scseg", - "roi_suffix": null, - "bids_path": "../duke/projects/ivado-medical-imaging/data_mice_abdullah-UQ/", - "random_seed": 1313, - "contrast_train_validation": ["t1"], - "contrast_balance": {}, - "contrast_test": ["t1"], - "center_test": [], - "batch_size": 8, - "dropout_rate": 0.3, - "batch_norm_momentum": 0.3, - "num_epochs": 200, - "initial_lr": 0.001, - "lr_scheduler": {"name": "CosineAnnealingWarmRestarts", "T_0": 20, "T_mult": 2}, - "loss": {"name": "dice"}, - "log_directory": "log_mice", - "film_layers": [0, 0, 0, 0, 0, 0, 0, 0], - "mixup_bool": false, - "mixup_alpha": 2, - "metadata": "contrast", - "missing_modality": false, - "multichannel": false, - "out_channel": 1, - "depth": 2, - "train_fraction": 0.6, - "test_fraction": 0.2, - "early_stopping_patience": 50, - "early_stopping_epsilon": 0.05, - "slice_axis": "axial", - "balance_samples": false, - "retrain_model": null, - "split_method": "per_patient", - "slice_filter": {"filter_empty_mask": true, "filter_empty_input": true}, - "slice_filter_roi": 10, - "attention_unet": false, - "uncertainty": {"epistemic": true, "aleatoric": false, "n_it": 10}, - "unet_3D": false, - "binarize_prediction": true, - "eval_params": {}, - "transformation_training": { - "Resample": { - "wspace": 0.04, - "hspace": 0.04 - }, - "CenterCrop": { - "size": [96, 96] - }, - "ElasticTransform": { - "alpha_range": [28.0, 30.0], - "sigma_range": [3.5, 4.5], - "p": 0.3 - }, - "RandomAffine": { - "degrees": 20, - "translate": [0.03, 0.03], - "scale": [0.98, 1.02] - }, - "NumpyToTensor": {}, - "NormalizeInstance": {"applied_to": ["im"]} - }, - "transformation_validation": { - "Resample": { - "wspace": 0.04, - "hspace": 0.04 - }, - "CenterCrop": { - "size": [96, 96] - }, - "NumpyToTensor": {}, - "NormalizeInstance": {"applied_to": ["im"]} - }, - "transformation_testing": { - "Resample": { - "wspace": 0.04, - "hspace": 0.04 - }, - "CenterCrop": { - "size": [96, 96] - }, - "NumpyToTensor": {}, - "NormalizeInstance": {"applied_to": ["im"]} - }, - "debugging": true + "gpu": 1, + "log_directory": "mice_sc", + "debugging": false, + "loader_parameters": { + "bids_path": "../duke/projects/ivado-medical-imaging/data_mice_abdullah-UQ/", + "target_suffix": ["_scseg"], + "roi_params": { + "suffix": null, + "slice_filter_roi": null + }, + "contrast_params": { + "training_validation": ["t1"], + "testing": ["t1"], + "balance": {} + }, + "slice_filter_params": { + "filter_empty_mask": true, + "filter_empty_input": true + }, + "slice_axis": "axial", + "multichannel": false + }, + "split_dataset": { + "fname_split": null, + "random_seed": 30, + "center_test": [], + "method": "per_patient", + "train_fraction": 0.6, + "test_fraction": 0.2 + }, + "training_parameters": { + "batch_size": 8, + "loss": { + "name": "DiceLoss" + }, + "training_time": { + "num_epochs": 200, + "early_stopping_patience": 50, + "early_stopping_epsilon": 0.05 + }, + "scheduler": { + "initial_lr": 0.001, + "lr_scheduler": { + "name": "CosineAnnealingWarmRestarts", + "T_0": 20, + "T_mult": 2 + } + }, + "balance_samples": false, + "mixup_alpha": null, + "transfer_learning": { + "retrain_model": null, + "retrain_fraction": 1.0 + } + }, + "default_model": { + "name": "Unet", + "dropout_rate": 0.3, + "bn_momentum": 0.3, + "depth": 2 + }, + "testing_parameters": { + "binarize_prediction": true, + "uncertainty": { + "epistemic": false, + "aleatoric": false, + "n_it": 1 + } + }, + "evaluation_parameters": { + "targetSize": {"unit": "vox", "thr": [20, 100]}, + "removeSmall": {"unit": "vox", "thr": 3}, + "overlap": {"unit": "vox", "thr": 3} + }, + "transformation": { + "Resample": + { + "wspace": 0.04, + "hspace": 0.04, + "preprocessing": true + }, + "CenterCrop": + { + "size": [96, 96], + "preprocessing": true + }, + "ElasticTransform": { + "alpha_range": [28.0, 30.0], + "sigma_range": [3.5, 4.5], + "p": 0.3, + "applied_to": ["im", "gt"], + "dataset_type": ["training"] + }, + "RandomAffine": { + "degrees": 20, + "translate": [0.03, 0.03], + "scale": [0.98, 1.02], + "dataset_type": ["training"] + }, + "NumpyToTensor": {}, + "NormalizeInstance": {"applied_to": ["im"]} + } }