{"url":"/dataset/lidc-idri","name":"LIDC-IDRI","full_name":"LIDC-IDRI","description_markdown":"The **LIDC-IDRI** dataset contains lesion annotations from four experienced thoracic radiologists. LIDC-IDRI contains 1,018 low-dose lung CTs from 1010 lung patients.\r\n\r\nSource: [A 3D Probabilistic Deep Learning System for Detection and Diagnosis of Lung Cancer Using Low-Dose CT Scans](https://arxiv.org/abs/1902.03233)\r\nImage Source: [https://thesai.org/Publications/ViewPaper?Volume=8&Issue=10&Code=IJACSA&SerialNo=15](https://thesai.org/Publications/ViewPaper?Volume=8&Issue=10&Code=IJACSA&SerialNo=15)","description_withheld":null,"homepage":"https://wiki.cancerimagingarchive.net/display/Public/LIDC-IDRI","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":null,"title":"The lung image database consortium (LIDC) and image database resource initiative (IDRI): a completed reference database of lung nodules on CT scans","first_author":null,"url":"http://dx.doi.org/10.1118/1.3528204"},"license":{"name":"Custom","url":"https://wiki.cancerimagingarchive.net/display/Public/LIDC-IDRI#1966254a2b592e6fba14f949f6e23bb1b7804cc"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Medical","url":"/datasets/modality/medical"}],"tasks":[{"name":"Neural Architecture Search","url":"/task/architecture-search","datasets_with_task":"/datasets/task/architecture-search"},{"name":"Lung Nodule Segmentation","url":"/task/lung-nodule-segmentation","datasets_with_task":"/datasets/task/lung-nodule-segmentation"},{"name":"Lung Nodule Detection","url":"/task/lung-nodule-detection","datasets_with_task":"/datasets/task/lung-nodule-detection"},{"name":"Lung Nodule Classification","url":"/task/lung-nodule-classification","datasets_with_task":"/datasets/task/lung-nodule-classification"},{"name":"Lung Nodule 3D Classification","url":"/task/lung-nodule-3d-classification","datasets_with_task":"/datasets/task/lung-nodule-3d-classification"},{"name":"Lung Nodule 3D Detection","url":"/task/lung-nodule-3d-detection","datasets_with_task":"/datasets/task/lung-nodule-3d-detection"}],"languages":[],"variants":["LIDC-IDRI"],"data_loaders":[{"repo":"https://github.com/Shwe234/himanshumajordataset","url":"https://github.com/Shwe234/himanshumajordataset","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/your-username/your-repository","url":"https://github.com/your-username/your-repository","frameworks":["pytorch"]}],"num_papers_in_archive":240,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/lung-nodule-classification-on-lidc-idri","task":"Lung Nodule Classification","dataset_variant":"LIDC-IDRI","rows":8,"metrics":["Accuracy","Acc","AUC","Accuracy(10-fold)","Recall/ Sensitivity","Precision","F1 Score"],"first_row_in_archive_order":{"model":"ProCAN","paper":"/paper/procan-progressive-growing-channel-attentive","metrics":{"AUC":"97.13","Accuracy":"94.11"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/lung-nodule-segmentation-on-lidc-idri","task":"Lung Nodule Segmentation","dataset_variant":"LIDC-IDRI","rows":2,"metrics":["IoU","Dice"],"first_row_in_archive_order":{"model":"ModelGenesis","paper":"/paper/models-genesis-generic-autodidactic-models","metrics":{"Dice":"75.86","IoU":"77.62"},"code_links":[{"title":"MrGiovanni/ModelsGenesis","url":"https://github.com/MrGiovanni/ModelsGenesis"},{"title":"cswin/AWC","url":"https://github.com/cswin/AWC"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/lung-nodule-3d-classification-on-lidc-idri","task":"Lung Nodule 3D Classification","dataset_variant":"LIDC-IDRI","rows":1,"metrics":["AUC"],"first_row_in_archive_order":{"model":"I3DR-Net","paper":"/paper/lung-nodule-detection-and-classification-from","metrics":{"AUC":"81.84"},"code_links":[{"title":"ivanwilliammd/I3DR-Net-Transfer-Learning","url":"https://github.com/ivanwilliammd/I3DR-Net-Transfer-Learning"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/lung-nodule-3d-detection-on-lidc-idri","task":"Lung Nodule 3D Detection","dataset_variant":"LIDC-IDRI","rows":1,"metrics":["AUC","mean average precision","Sensitivity"],"first_row_in_archive_order":{"model":"I3DR-Net","paper":"/paper/lung-nodule-detection-and-classification-from","metrics":{"AUC":"81.84","Sensitivity":"94.12","mean average precision":"49.61"},"code_links":[{"title":"ivanwilliammd/I3DR-Net-Transfer-Learning","url":"https://github.com/ivanwilliammd/I3DR-Net-Transfer-Learning"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/lung-nodule-detection-on-lidc-idri","task":"Lung Nodule Detection","dataset_variant":"LIDC-IDRI","rows":1,"metrics":["AUC","mean average precision","Sensitivity"],"first_row_in_archive_order":{"model":"I3DR-Net","paper":"/paper/lung-nodule-detection-and-classification-from","metrics":{"AUC":"81.84","Sensitivity":"94.12","mean average precision":"49.61"},"code_links":[{"title":"ivanwilliammd/I3DR-Net-Transfer-Learning","url":"https://github.com/ivanwilliammd/I3DR-Net-Transfer-Learning"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/neural-architecture-search-on-lidc-idri","task":"Neural Architecture Search","dataset_variant":"LIDC-IDRI","rows":1,"metrics":["F1 score","Specificity (VEB+)"],"first_row_in_archive_order":{"model":"NASLung (ours)","paper":"/paper/learning-efficient-explainable-and","metrics":{"F1 score":"0.8929","Specificity (VEB+)":"95.04"},"code_links":[{"title":"fei-hdu/NAS-Lung","url":"https://github.com/fei-hdu/NAS-Lung"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/medical-slice-transformer-improved-diagnosis","title":"Medical Slice Transformer: Improved Diagnosis and Explainability on 3D Medical Images with DINOv2","date":"2024-11-24","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/variational-autoencoders-for-feature-1","title":"Variational Autoencoders for Feature Exploration and Malignancy Prediction of Lung Lesions","date":"2023-11-27","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/learning-efficient-explainable-and","title":"Learning Efficient, Explainable and Discriminative Representations for Pulmonary Nodules Classification","date":"2021-01-19","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/procan-progressive-growing-channel-attentive","title":"ProCAN: Progressive Growing Channel Attentive Non-Local Network for Lung Nodule Classification","date":"2020-10-29","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/learning-semantics-enriched-representation","title":"Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration","date":"2020-07-14","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/lung-nodule-detection-and-classification-from","title":"Lung nodule detection and classification from Thorax CT-scan using RetinaNet with transfer learning","date":"2020-04-08","rows_on_this_dataset":4,"code_links":1,"syntology":null},{"paper":"/paper/models-genesis-generic-autodidactic-models","title":"Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis","date":"2019-08-19","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/lung-nodule-classification-using-deep-local","title":"Lung Nodule Classification using Deep Local-Global Networks","date":"2019-04-23","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/gated-dilated-networks-for-lung-nodule","title":"Gated-Dilated Networks for Lung Nodule Classification in CT scans","date":"2019-01-01","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/deeplung-deep-3d-dual-path-nets-for-automated","title":"DeepLung: Deep 3D Dual Path Nets for Automated Pulmonary Nodule Detection and Classification","date":"2018-01-25","rows_on_this_dataset":1,"code_links":2,"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."}