Name | DL | Torrents | Total Size | Joe's Recommended Mirror List [edit] | 233 | 8.28TB | 1827 | 0 | Computer Vision [edit] | 79 | 1.41TB | 560 | 0 | Medical [edit] | 87 | 2.20TB | 725 | 0 | Chest Xray [edit] | 12 | 1.22TB | 130 | 0 |
SIIM_TRAIN_TEST (15295 files)
dicom-images-test/_/_/ID_0a0adf93f.dcm | 162.13kB |
dicom-images-test/_/_/ID_0a4f3c934.dcm | 160.25kB |
dicom-images-test/_/_/ID_0a9b7968a.dcm | 110.08kB |
dicom-images-test/_/_/ID_0a50c0cc7.dcm | 125.62kB |
dicom-images-test/_/_/ID_0a323a5be.dcm | 109.56kB |
dicom-images-test/_/_/ID_0a920cc01.dcm | 164.54kB |
dicom-images-test/_/_/ID_0a4674064.dcm | 73.24kB |
dicom-images-test/_/_/ID_0ab3c2234.dcm | 157.77kB |
dicom-images-test/_/_/ID_0ac3e69bc.dcm | 149.83kB |
dicom-images-test/_/_/ID_0acfa68b1.dcm | 120.24kB |
dicom-images-test/_/_/ID_0aeb72cba.dcm | 120.10kB |
dicom-images-test/_/_/ID_0b0a1315d.dcm | 149.47kB |
dicom-images-test/_/_/ID_0b2da875a.dcm | 161.69kB |
dicom-images-test/_/_/ID_0b7d6530c.dcm | 142.47kB |
dicom-images-test/_/_/ID_0b27bd5c2.dcm | 157.28kB |
dicom-images-test/_/_/ID_0ba83217f.dcm | 163.28kB |
dicom-images-test/_/_/ID_0bb960c48.dcm | 149.21kB |
dicom-images-test/_/_/ID_0bbbdda07.dcm | 79.14kB |
dicom-images-test/_/_/ID_0bc787781.dcm | 120.91kB |
dicom-images-test/_/_/ID_0beb4899d.dcm | 164.45kB |
dicom-images-test/_/_/ID_0bf00babd.dcm | 108.32kB |
dicom-images-test/_/_/ID_0bfd328b9.dcm | 122.02kB |
dicom-images-test/_/_/ID_0c026cd43.dcm | 100.54kB |
dicom-images-test/_/_/ID_0c6cb4607.dcm | 163.22kB |
dicom-images-test/_/_/ID_0c7f391f7.dcm | 125.78kB |
dicom-images-test/_/_/ID_0c8fca435.dcm | 177.32kB |
dicom-images-test/_/_/ID_0c902c890.dcm | 141.58kB |
dicom-images-test/_/_/ID_0c1737948.dcm | 122.81kB |
dicom-images-test/_/_/ID_0c4816508.dcm | 133.74kB |
dicom-images-test/_/_/ID_0cbc86b48.dcm | 125.45kB |
dicom-images-test/_/_/ID_0cd589ea0.dcm | 120.68kB |
dicom-images-test/_/_/ID_0d5bf2c18.dcm | 158.95kB |
dicom-images-test/_/_/ID_0d56b5fd2.dcm | 144.30kB |
dicom-images-test/_/_/ID_0d90d4adc.dcm | 141.02kB |
dicom-images-test/_/_/ID_0d735ae70.dcm | 134.03kB |
dicom-images-test/_/_/ID_0d2016b4a.dcm | 151.46kB |
dicom-images-test/_/_/ID_0d98731cd.dcm | 106.81kB |
dicom-images-test/_/_/ID_0da60ddc7.dcm | 152.87kB |
dicom-images-test/_/_/ID_0dba743ec.dcm | 121.32kB |
dicom-images-test/_/_/ID_0dd0433f5.dcm | 149.88kB |
dicom-images-test/_/_/ID_0dfa94b38.dcm | 159.49kB |
dicom-images-test/_/_/ID_0e0ebf53a.dcm | 122.77kB |
dicom-images-test/_/_/ID_0e1e5591e.dcm | 102.21kB |
dicom-images-test/_/_/ID_0e44bcf40.dcm | 161.55kB |
dicom-images-test/_/_/ID_0e52a91c4.dcm | 113.66kB |
dicom-images-test/_/_/ID_0e63f6a3c.dcm | 145.62kB |
dicom-images-test/_/_/ID_0e70e5aff.dcm | 164.91kB |
dicom-images-test/_/_/ID_0e35418bf.dcm | 178.25kB |
dicom-images-test/_/_/ID_0e6781865.dcm | 114.27kB |
Type: Dataset
Tags: radiology
Bibtex:
Tags: radiology
Bibtex:
@article{, title= {SIIM-ACR Pneumothorax Segmentation}, keywords= {radiology}, author= {Society for Imaging Informatics in Medicine (SIIM)}, abstract= {In this competition, you’ll develop a model to classify (and if present, segment) pneumothorax from a set of chest radiographic images. If successful, you could aid in the early recognition of pneumothoraces and save lives. What am I predicting? We are attempting to a) predict the existence of pneumothorax in our test images and b) indicate the location and extent of the condition using masks. Your model should create binary masks and encode them using RLE. https://i.imgur.com/xJYwEv4.png}, terms= {}, license= {}, superseded= {}, url= {https://www.kaggle.com/c/siim-acr-pneumothorax-segmentation} }