Name | DL | Torrents | Total Size |
DSB3 (3 files)
stage1_labels.csv | 55.84kB |
stage2.7z | 97.83GB |
stage1.7z | 66.23GB |
Type: Dataset
Tags:
Bibtex:
Tags:
Bibtex:
@article{, title= {Data Science Bowl 2017 Lung Cancer Detection (DSB3) }, keywords= {}, author= {}, abstract= {In this dataset, you are given over a thousand low-dose CT images from high-risk patients in DICOM format. Each image contains a series with multiple axial slices of the chest cavity. Each image has a variable number of 2D slices, which can vary based on the machine taking the scan and patient. The DICOM files have a header that contains the necessary information about the patient id, as well as scan parameters such as the slice thickness. ``` stage1.7z: 285380 dcm files stage2.7z: 186160 dcm files stage1_labels.csv: 1595 labels ``` }, terms= {}, license= {}, superseded= {}, url= {https://www.kaggle.com/c/data-science-bowl-2017/data} }