{"url":"/dataset/extended-heartseg","name":"Extended heartSeg","full_name":null,"description_markdown":"The dataset X of this work is an extension of the heartSeg dataset. Each sample x ∈ X is an RGB image capturing the heart region of Medaka (Oryzias latipes) hatchlings from a constant ventral view. Since the body of Medaka is see-through, noninvasive studies regarding the internal organs and the whole circulatory system are practicable. A Medaka’s heart contains three parts: the atrium, the ventricle, and the bulbus. The atrium receives deoxygenated blood from the circulatory system and delivers it to the ventricle, which forwards it into the bulbus. The bulbus is the heart’s exit chamber and provides the gill arches with a constant blood flow. The blood flow through these three chambers was captured in 63 short recordings (around 11 seconds with 24 frames per second each) in total, from which the single image samples x ∈ X are extracted. The dataset is split into training and test data following the heartSeg dataset with ntrain = 565 samples in the training set Xtrain and ntest = 165 samples in the test set Xtest. The RGB image samples have a 640 × 480 pixels resolution.","description_withheld":null,"homepage":"https://osf.io/uyk79/","introduced_date":"2022-02-08","introduced_date_note":null,"introduced_by":{"paper":"/paper/methods-for-the-frugal-labeler-multi-class","title":"Methods for the frugal labeler: Multi-class semantic segmentation on heterogeneous labels","first_author":"Mark Schutera","url":null},"license":{"name":"Unknown","url":"https://osf.io/uyk79/"},"modalities":[{"name":"Videos","url":"/datasets/modality/videos"},{"name":"Biology","url":"/datasets/modality/biology"},{"name":"Biomedical","url":"/datasets/modality/biomedical"},{"name":"Medical","url":"/datasets/modality/medical"}],"tasks":[{"name":"2D Semantic Segmentation","url":"/task/2d-semantic-segmentation","datasets_with_task":"/datasets/task/2d-semantic-segmentation"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Extended heartSeg"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/2d-semantic-segmentation-on-extended-heartseg","task":"2D Semantic Segmentation","dataset_variant":"Extended heartSeg","rows":1,"metrics":["Average IOU"],"first_row_in_archive_order":{"model":"UNet","paper":"/paper/methods-for-the-frugal-labeler-multi-class","metrics":{"Average IOU":"0.84"},"code_links":[{"title":"Heterogeneous-Semantic-Segmentation/Utilities-for-The-Frugal-Labeler","url":"https://github.com/Heterogeneous-Semantic-Segmentation/Utilities-for-The-Frugal-Labeler"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/methods-for-the-frugal-labeler-multi-class","title":"Methods for the frugal labeler: Multi-class semantic segmentation on heterogeneous labels","date":"2022-02-08","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+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."}