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Published May 2, 2022 | Version v4

Results of IMC-Denoise: a content aware pipeline to enhance Imaging Mass Cytometry

Authors/Creators

  • 1. Washington University in St. Louis

Description

  • Generated training sets:
    • training_set_supp_table6.zip
    • training_set_supp_table7.zip
    • training_set_supp_table8.zip
    • training_set_supp_table9.zip
    • training_set_supp_table10.zip
    • training_set_supp_table11.zip
  • Trained weights of experimental data:
    • training_result_supp_table7.zip
    • training_result_supp_table8.zip
    • training_result_supp_table9.zip
    • training_result_supp_table10.zip
    • training_result_supp_table11.zip
  • Simulation results:
    • Simulation_results.zip
  • Experimental results:
    • Human_bone_marrow_IMC_denoising_results.zip
    • Human_breast_cancer_IMC_denoising_results.zip
    • Human_pancreatic_cancer_IMC_denoising_results.zip
    • MIBI_denoising_results.zip
  • Ilastik-processed or manual-labeled results:
    • DIMR_Ilastik_results.zip
    • background_removal_results.zip
    • manual_annotated_public_datasets.zip
  • Extracted single cell data and the corresponding phenotyping results:
    • single_cell_analysis.zip

Files

background_removal_results.zip

Files (45.1 GB)

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