folder LNDb (240 files)
fileLNDb-0001.zip 114.89MB
fileLNDb-0002.zip 91.65MB
fileLNDb-0003.zip 108.99MB
fileLNDb-0004.zip 114.49MB
fileLNDb-0005.zip 118.99MB
fileLNDb-0007.zip 92.43MB
fileLNDb-0008.zip 112.34MB
fileLNDb-0010.zip 106.83MB
fileLNDb-0011.zip 121.45MB
fileLNDb-0013.zip 133.77MB
fileLNDb-0015.zip 116.84MB
fileLNDb-0016.zip 116.80MB
fileLNDb-0017.zip 99.71MB
fileLNDb-0018.zip 117.25MB
fileLNDb-0020.zip 111.99MB
fileLNDb-0021.zip 117.82MB
fileLNDb-0022.zip 118.72MB
fileLNDb-0024.zip 125.19MB
fileLNDb-0025.zip 115.42MB
fileLNDb-0026.zip 112.61MB
fileLNDb-0028.zip 130.62MB
fileLNDb-0031.zip 123.81MB
fileLNDb-0034.zip 111.32MB
fileLNDb-0035.zip 102.88MB
fileLNDb-0037.zip 111.30MB
fileLNDb-0039.zip 121.49MB
fileLNDb-0041.zip 125.67MB
fileLNDb-0043.zip 112.33MB
fileLNDb-0044.zip 104.17MB
fileLNDb-0046.zip 112.01MB
fileLNDb-0048.zip 110.19MB
fileLNDb-0049.zip 123.93MB
fileLNDb-0050.zip 119.74MB
fileLNDb-0051.zip 103.06MB
fileLNDb-0052.zip 98.47MB
fileLNDb-0053.zip 105.45MB
fileLNDb-0055.zip 110.77MB
fileLNDb-0056.zip 104.78MB
fileLNDb-0059.zip 110.97MB
fileLNDb-0060.zip 132.73MB
fileLNDb-0061.zip 128.68MB
fileLNDb-0062.zip 111.20MB
fileLNDb-0063.zip 117.44MB
fileLNDb-0064.zip 125.39MB
fileLNDb-0065.zip 116.50MB
fileLNDb-0066.zip 100.15MB
fileLNDb-0067.zip 120.41MB
fileLNDb-0068.zip 115.55MB
fileLNDb-0069.zip 102.60MB
Too many files! Click here to view them all.
Type: Dataset
Tags:

Bibtex:
@article{,
title= {LNDb CT scan dataset (training)},
keywords= {},
author= {João Pedrosa and Guilherme Aresta and Carlos Ferreira and Márcio Rodrigues and Patrícia Leitão and André Silva Carvalho and João Rebelo and Eduardo Negrão and Isabel Ramos and António Cunha and Aurélio Campilho},
abstract= {The main goal of this challenge is the automatic classification of chest CT scans according to the 2017 Fleischner society pulmonary nodule guidelines for patient follow-up recommendation. 

The LNDb dataset 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. Further details on patient selection and data acquisition can be consulted on the database description paper.

Each CT scan was read by at least one radiologist at CHUSJ to identify pulmonary nodules and other suspicious lesions. A total of 5 radiologists with at least 4 years of experience reading up to 30 CTs per week participated in the annotation process throughout the project. Annotations were performed in a single blinded fashion, i.e. a radiologist would read the scan once and no consensus or review between the radiologists was performed. Each scan was read by at least one radiologist. The instructions for manual annotation were adapted from LIDC-IDRI. Each radiologist identified the following lesions:

 - nodule ⩾3mm: any lesion considered to be a nodule by the radiologist with greatest in-plane dimension larger or equal to 3mm;
 - nodule <3mm: any lesion considered to be a nodule by the radiologist with greatest in-plane dimension smaller than 3mm;
 - non-nodule: any pulmonary lesion considered not to be a nodule by the radiologist, but that contains features which could make it identifiable as a nodule;

The annotation process varied for the different categories. Nodules ⩾3mm were segmented and subjectively characterized according to LIDC-IDRI (ratings on subtlety, internal structure, calcification, sphericity, margin, lobulation, spiculation, texture and likelihood of malignancy). For a complete description of these characteristics the reader is referred to McNitt-Gray et al.. For nodules <3mm the nodule centroid was marked and subjective assessment of the nodule's characteristics was performed. For non-nodules, only the lesion centroid was marked. Given that different radiologists may have read the same CT and no consensus review was performed, variability in radiologist annotations is expected.

Note that from the 294 CTs of the LNDb dataset, 58 CTs with annotations by at least two radiologists have been withheld for the test set, as well as the corresponding annotations.

https://i.imgur.com/MiHSh9c.png},
terms= {The dataset, or any data derived from it, cannot be given or redistributed under any circumstances to persons not belonging to the registered team. If the data in the dataset is remixed, transformed or built upon, the modified data cannot be redistributed under any circumstances;

The dataset cannot be used for commercial purposed under any circumstances;

Appropriate credit must be given to the authors any time this data is used, independent of purpose. Attribution must be done through citation of the database description paper (https://arxiv.org/abs/1911.08434) or (after publication) to the main challenge publication.},
license= {https://creativecommons.org/licenses/by-nc-nd/4.0/},
superseded= {},
url= {https://lndb.grand-challenge.org/Data/}
}

Hosted by users:

Send Feedback