{"url":"/dataset/jsrt-negative-formats","name":"JSRT (negative formats)","full_name":"JSRT (negative formats)","description_markdown":"We processed 241 pairs of CXR and DES soft tissue images from the JSRT dataset by performing operations like inversion and contrast adjustment to convert these images into negative formats more frequently used in clinical settings.","description_withheld":null,"homepage":"https://benny0323.github.io/BS-LDM-Project-Page/","introduced_date":"2024-12-20","introduced_date_note":null,"introduced_by":{"paper":"/paper/bs-ldm-effective-bone-suppression-in-high","title":"BS-LDM: Effective Bone Suppression in High-Resolution Chest X-Ray Images with Conditional Latent Diffusion Models","first_author":"Yifei Sun","url":null},"license":{"name":"MIT","url":"https://github.com/diaoquesang/BS-LDM/blob/main/LICENSE"},"modalities":[{"name":"Medical","url":"/datasets/modality/medical"}],"tasks":[{"name":"Bone Suppression From Dual Energy Chest X-Rays","url":"/task/bone-suppression-from-dual-energy-chest-x","datasets_with_task":"/datasets/task/bone-suppression-from-dual-energy-chest-x"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["JSRT (negative formats)"],"data_loaders":[{"repo":"https://github.com/diaoquesang/BS-LDM","url":"https://github.com/diaoquesang/BS-LDM/","frameworks":["tf","pytorch","jax"]}],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"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."}