{"url":"/dataset/histoartifacts","name":"HistoArtifacts","full_name":null,"description_markdown":"This dataset contains five notable histological artifacts: blur, blood (hemorrhage), air bubbles, folded tissue, and damaged tissue. This dataset is used in the following works, and a description of the dataset can be found at https://zenodo.org/records/10809442.\r\n\r\nSee detailed video explanation in the video paper: https://www.sciencetalks-journal.com/article/S2772-5693(24)00013-6/fulltext","description_withheld":null,"homepage":"https://zenodo.org/records/10809442","introduced_date":"2024-03-12","introduced_date_note":null,"introduced_by":{"paper":"/paper/equipping-computational-pathology-systems","title":"Equipping Computational Pathology Systems with Artifact Processing Pipelines: A Showcase for Computation and Performance Trade-offs","first_author":"Neel Kanwal","url":null},"license":{"name":"Creative Commons Attribution 4.0 International","url":null},"modalities":[],"tasks":[{"name":"Anomaly Detection","url":"/task/anomaly-detection","datasets_with_task":"/datasets/task/anomaly-detection"},{"name":"Defocus Blur Detection","url":"/task/defocus-blur-detection","datasets_with_task":"/datasets/task/defocus-blur-detection"},{"name":"Artifact Detection","url":"/task/artifact-detection","datasets_with_task":"/datasets/task/artifact-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["HistoArtifacts"],"data_loaders":[],"num_papers_in_archive":4,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/artifact-detection-on-histoartifacts","task":"Artifact Detection","dataset_variant":"HistoArtifacts","rows":5,"metrics":["MCC","Average F1","1:1 Accuracy","ACC","AUROC","Avg F1","F1","Recall/ Sensitivity"],"first_row_in_archive_order":{"model":"DKL_101010","paper":"/paper/are-you-sure-its-an-artifact-artifact","metrics":{"1:1 Accuracy":"0.9952","AUROC":"0.995","Average F1":"0.996","MCC":"0.990"},"code_links":[{"title":"NeelKanwal/Vision-Transformers-for-Small-Histological-Datasets-Learned-Through-Knowledge-Distillation","url":"https://github.com/NeelKanwal/Vision-Transformers-for-Small-Histological-Datasets-Learned-Through-Knowledge-Distillation"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/equipping-computational-pathology-systems","title":"Equipping Computational Pathology Systems with Artifact Processing Pipelines: A Showcase for Computation and Performance Trade-offs","date":"2024-03-12","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/are-you-sure-its-an-artifact-artifact","title":"Are you sure it’s an artifact? Artifact detection and uncertainty quantification in histological images","date":"2023-12-23","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/vision-transformers-for-small-histological","title":"Vision Transformers for Small Histological Datasets Learned through Knowledge Distillation","date":"2023-05-27","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/quantifying-the-effect-of-color-processing-on","title":"Quantifying the effect of color processing on blood and damaged tissue detection in Whole Slide Images","date":"2022-09-26","rows_on_this_dataset":2,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}