Data Science Bowl 2017 Lung Cancer Detection (DSB3)

DSB3 (3 files)
stage1.7z 66.23GB
stage1_labels.csv 55.84kB
stage2.7z 97.83GB
Type: Dataset
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superseded= {},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}
}


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10 day statistics (3 downloads taking more than 30 seconds)

Average Time 4 hours, 22 minutes, 46 seconds
Average Speed 10.41MB/s
Best Time 17 minutes, 07 seconds
Best Speed 159.74MB/s
Worst Time 10 hours, 08 minutes, 42 seconds
Worst Speed 4.49MB/s
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