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arrow_drop_down Pancreas-CT Dataset arrow_drop_down folder images arrow_right folder lists insert_drive_file 0001.npy insert_drive_file 0002.npy insert_drive_file 0003.npy insert_drive_file 0004.npy insert_drive_file 0005.npy insert_drive_file 0006.npy insert_drive_file 0007.npy insert_drive...
Development of a volumetric pancreas segmentation CT dataset for AI applications through trained technologists: a study during the COVID 19 containment phaseDeep learningData curationArtificial intelligenceCOVID-19To evaluate the performance of trained technologists vis-脿-vis radiologists for volumetric ...
python -m monai.bundle run --config_file configs/train.yaml --dataset_dir <actual dataset path> Override thetrainconfig to execute multi-GPU training: torchrun --nnodes=1 --nproc_per_node=8 -m monai.bundle run --config_file "['configs/train.yaml','configs/multi_gpu_train.yaml']" ...
Methods Approach Dataset Performance / Dice Attention U-Net: Learning Where to Look for the Pancreas oktay2018attentionunet Attention mechanisms (layers) are integrated within the U-Net to focus on the pancreas region to avoid false positives. NIH (8) 83.1 ± 3.8 Fully automated pancreas segmentat...
Our method was evaluated on both public NIH pancreas dataset and local hospital dataset, and achieved an average Dice-Srensen Coefficient (DSC) value of 85.49±4.77% on the NIH dataset, outperforming former coarse-to-fine methods. 展开
We evaluate our approach on the NIH pancreas segmentation dataset, andoutperform the state-of-the-art by more than 4%, measured by the averageDice-S{\o}rensen Coefficient (DSC). In addition, we report 62.43% DSC in theworst case, which guarantees the reliability of our approach in ...
周纵苇 AbdomenAtlas-8K | GitHub:链接 We are proud to introduce AbdomenAtlas-8K, a substantial multi-organ dataset with the spleen, liver, kidneys, stomach, gallbladder, pancreas, aorta, and IVC annotated in 8,448 CT volumes, totaling 3.2 million CT slices. ...
Development of a volumetric pancreas segmentation CT dataset for AI applications through trained technologists: a study during the COVID 19 containment phasePurpose: To evaluate the performance of trained technologists vis-脿-vis radiologists for volumetric pancreas segmentation and to assess the impact ...
Leaderboard Dataset View by DICE (AVERAGE)AD-MTAD-MTOther modelsModels with highest Dice (Average)29. Nov80.21 Filter: untagged Edit Leaderboard RankModelDice (Average)PaperCodeResultYearTags 1 AD-MT 80.21 Alternate Diverse Teaching for Semi-supervised Medical Image Segmentation 2023Contact...