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add skm-tea models trained for Neurips D&B Track (2021)
8b8b105
AUG_TEST:
UNDERSAMPLE:
ACCELERATIONS:
- 6
AUG_TRAIN:
NOISE_P: 0.2
UNDERSAMPLE:
ACCELERATIONS:
- 6
CALIBRATION_SIZE: 24
CENTER_FRACTIONS: []
NAME: PoissonDiskMaskFunc
PRECOMPUTE:
NUM: 100000
SEED: -1
USE_NOISE: false
CUDNN_BENCHMARK: false
DATALOADER:
ALT_SAMPLER:
PERIOD_SUPERVISED: 1
PERIOD_UNSUPERVISED: 1
DATA_KEYS: []
DROP_LAST: true
FILTER:
BY: []
GROUP_SAMPLER:
AS_BATCH_SAMPLER: true
BATCH_BY:
- num_coils
- matrix_shape
NUM_WORKERS: 8
PREFETCH_FACTOR: 2
SAMPLER_TRAIN: GroupSampler
SUBSAMPLE_TRAIN:
NUM_TOTAL: -1
NUM_TOTAL_BY_GROUP: []
NUM_UNDERSAMPLED: 0
NUM_VAL: -1
NUM_VAL_BY_GROUP: []
SEED: 1000
DATASETS:
QDESS:
DATASET_TYPE: ''
ECHO_KIND: echo1+echo2
KWARGS: []
TEST:
- stanford_qdess_v0.1.0_test
TRAIN:
- stanford_qdess_v0.1.0_train
VAL:
- stanford_qdess_v0.1.0_val
DESCRIPTION:
BRIEF: Recon only unet baseline - 4 pooling layers, 32 channels, L1 loss, lr=1e-3,
echo=echo1+echo2, acc=6
ENTITY_NAME: mtrecon
EXP_NAME: recon-baseline/unet-6x-echo1+echo2/version_002
PROJECT_NAME: mtrecon
TAGS:
- neurips
- recon-baseline
- baseline
- unet
- unet_6x
MODEL:
CASCADE:
ITFS:
PERIOD: 0
RECON_MODEL_NAME: ''
SEG_MODEL_NAME: ''
SEG_NORMALIZE: ''
USE_MAGNITUDE: false
ZERO_FILL: false
CS:
MAX_ITER: 200
REGULARIZATION: 0.005
DENOISING:
META_ARCHITECTURE: GeneralizedUnrolledCNN
NOISE:
STD_DEV:
- 1
USE_FULLY_SAMPLED_TARGET: true
USE_FULLY_SAMPLED_TARGET_EVAL: null
DEVICE: cpu
META_ARCHITECTURE: UnetModel
N2R:
META_ARCHITECTURE: GeneralizedUnrolledCNN
USE_SUPERVISED_CONSISTENCY: false
NORMALIZER:
KEYWORDS: []
NAME: TopMagnitudeNormalizer
PARAMETERS:
INIT: []
USE_COMPLEX_WEIGHTS: false
RECON_LOSS:
NAME: l1
RENORMALIZE_DATA: false
WEIGHT: 1.0
SEG:
ACTIVATION: sigmoid
CLASSES: []
INCLUDE_BACKGROUND: false
IN_CHANNELS: null
LOSS_NAME: DiceLoss
LOSS_WEIGHT: 1.0
MODEL:
DYNUNET_MONAI:
DEEP_SUPERVISION: false
DEEP_SUPR_NUM: 1
KERNEL_SIZE:
- 3
NORM_NAME: instance
RES_BLOCK: false
STRIDES:
- 1
UPSAMPLE_KERNEL_SIZE:
- 2
UNET_MONAI:
ACTIVATION:
- prelu
- {}
CHANNELS: []
DROPOUT: 0.0
KERNEL_SIZE:
- 3
NORM:
- instance
- {}
NUM_RES_UNITS: 0
STRIDES: []
UP_KERNEL_SIZE:
- 3
VNET_MONAI:
ACTIVATION:
- elu
- inplace: true
DROPOUT_DIM: 3
DROPOUT_PROB: 0.5
USE_MAGNITUDE: true
TASKS:
- recon
TB_RECON:
CHANNELS:
- 16
- 32
- 64
DEC_NUM_CONV_BLOCKS:
- 2
- 3
ENC_NUM_CONV_BLOCKS:
- 1
- 2
- 3
KERNEL_SIZE:
- 5
MULTI_CONCAT: []
ORDER:
- conv
- relu
STRIDES:
- 2
USE_MAGNITUDE: false
UNET:
BLOCK_ORDER:
- conv
- instancenorm
- - leakyrelu
- negative_slope: 0.2
- dropout
CHANNELS: 32
DROPOUT: 0.0
IN_CHANNELS: 2
NUM_POOL_LAYERS: 4
OUT_CHANNELS: 2
UNROLLED:
CONV_BLOCK:
ACTIVATION: relu
NORM: none
NORM_AFFINE: false
ORDER:
- norm
- act
- drop
- conv
DROPOUT: 0.0
FIX_STEP_SIZE: false
KERNEL_SIZE:
- 3
NUM_EMAPS: 1
NUM_FEATURES: 256
NUM_RESBLOCKS: 2
NUM_UNROLLED_STEPS: 5
PADDING: ''
SHARE_WEIGHTS: false
WEIGHTS: ''
OUTPUT_DIR: results://skm-tea/neurips2021/6x/U-Net_E1+E2
SEED: 1000
SOLVER:
BASE_LR: 0.001
CHECKPOINT_MONITOR: val_loss
CHECKPOINT_PERIOD: 1
EARLY_STOPPING:
MIN_DELTA: 0.0
MONITOR: val_loss
PATIENCE: 0
GAMMA: 1.0
GRAD_ACCUM_ITERS: 1
LR_SCHEDULER_NAME: ''
MAX_ITER: 20
MIN_LR: null
MOMENTUM: 0.9
OPTIMIZER: Adam
STEPS: []
TEST_BATCH_SIZE: 16
TRAIN_BATCH_SIZE: 24
WARMUP_FACTOR: 0.001
WARMUP_ITERS: 1000
WARMUP_METHOD: linear
WEIGHT_DECAY: 0.0001
WEIGHT_DECAY_NORM: 0.0
TEST:
EVAL_PERIOD: 1
EXPECTED_RESULTS: []
FLUSH_PERIOD: 1000
QDESS_EVALUATOR:
ADDITIONAL_PATHS: []
VAL_METRICS:
RECON:
- psnr
- psnr_scan
- psnr_mag
- psnr_mag_scan
- nrmse
- nrmse_scan
- nrmse_mag
- nrmse_mag_scan
- ssim (Wang)
SEM_SEG: []
TIME_SCALE: epoch
VERSION: 1
VIS_PERIOD: -400