Open rohanbanerjee opened 5 months ago
Experiment 1: To check if changing the default spacing configured by the nnunetv2_preprocess
affects the model performace
How Customize the spacing hyperparameter (instructions). Attaching the nnUnetv2 plan for this below: nnUNetPlans.json To reproduce the experiment, run the following command:
nnUNetv2_preprocess -d <DATASET_ID> -c 3d_fullres_1_spacing -np 1
Attaching the QC for qualitative results: held-out_test_common_1_bids_qc.zip
Experiment 2: To check if changing the default patch_size
configured by the nnunetv2_preprocess
affects the model performace
How Customize the spacing hyperparameter (instructions). Attaching the nnUnetv2 plan for this below: nnUNetPlans.json To reproduce the experiment, run the following command:
nnUNetv2_preprocess -d <DATASET_ID> -c 3d_fullres_mod_patch_size -np 1
Attaching the QC for qualitative results: held-out_test_common_mod_patch_size_bids_qc.zip
The goal of this issue is to track the training and performance of a single model(s) (instead of fine-tuning).
Result comparisons and observations: report
Steps involved:
data_superset
from now on)nnunetv2_preprocess
(here) and train a model. The plan configured by nnUNetv2 is attached below: nnUNetPlans.json To reproduce the experiment, run the following command:After the training was completed inference was run on the
held-out_test
set (#33) using this scriptNote: This process is repeated for all the following comments also:
Attaching the QC for qualitative results: held-out_test_common_bids_qc.zip