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The Lung Nodule Database (LNDb) was developed as an external dataset complimentary to LIDCIDRI. The publication of this database gives continuity to LIDC-IDRI and allows the community to perform an external and comparable validation of proposed computer-aided diagnosis (CAD) systems. The LNDb contains 294 CT scans collected retrospectively at the Centro Hospitalar e Universitário de São João (CHUSJ) in Porto, Portugal between 2016 and 2018. All data was acquired under approval from the CHUSJ Ethical Commitee and was anonymised prior to any analysis to remove personal information except for patient birth year and gender. The database served as the basis for the Grand Challenge on automatic lung cancer patient management, or LNDb challenge. THIS DATASET IS PUBLICALLY AVAILABLE UNDER A CREATIVE COMMONS CC BY-NC-ND LICENSE (ATTRIBUTION-NONCOMMERCIAL-NODERIVS) ESSENCIALLY, YOU ARE GRANTED ACCESS TO THE DATASET FOR USE IN YOUR RESEARCH AS LONG AS YOU CREDIT OUR WORK/PUBLICATIONS(*), BUT YOU CANNOT CHANGE THEM IN ANY WAY OR USE THEM COMMERCIALLY (*) Pedrosa, João, et al. "LNDb: a lung nodule database on computed tomography." arXiv preprint arXiv:1911.08434 (2019). (*) Pedrosa, João, et al. "LNDb challenge on automatic lung cancer patient management." Medical image analysis 70 (2021): 102027.
This work was financed by the European Regional Development Fund (ERDF) through the Operational Programme for Competitiveness - COMPETE 2020 Programme and by National Funds through the Portuguese Funding agency, FCT Fundaçãoo para a Ciência e Tecnologia within project PTDC/EEI-SII/6599/2014 (POCI01-0145-FEDER-016673).
{"references": ["Pedrosa, Jo\u00e3o, et al. \"LNDb: a lung nodule database on computed tomography.\"\u00a0arXiv preprint arXiv:1911.08434\u00a0(2019).", "Pedrosa, Jo\u00e3o, et al. \"LNDb challenge on automatic lung cancer patient management.\"\u00a0Medical image analysis\u00a070 (2021): 102027."]}
lung cancer, follow-up recommendation, challenge, pulmonary nodules, low dose computed tomography
lung cancer, follow-up recommendation, challenge, pulmonary nodules, low dose computed tomography
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