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First look at dataset
Valentyn1997 edited this page Jan 29, 2020
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Report of unusual cases - notebook
- Detect anomalies in hand xray images
- Should work on unlabeled data → can't use classification task
- First step: to detect obvious anomalies like metal plates (e.g.)
Data is a subset of this dataset: MURA. "Study is manually labeled by ra- diologists as either normal or abnormal. To evaluate models robustly and to get an estimate of radiologist performance, we collect additional labels from six board- certified Stanford radiologists on the test set, consisting of 207 musculoskeletal studies. On this test set, the majority vote of a group of three radiologists serves as gold standard" (see abstract).
The range of amount of image ranges from 1 to 5 per study. One person can have more than one study. Most of the studies consist of 2-3 images.
More than 1400 studies are normal. About 500 studies are not normal.
- The images have a frame around the hand → can influence the model
- The frame can vary
- Background color is not fixed
- Noisy
- Text labels, sometimes more than one
- Arrow in the image
- Different size
is classified as normal