The TMED-2 dataset used in our experiments contains
view_and_diagnosis_labeled_set: 599 studies from 577 unique patients (some patients have multiple studies on distinct days).- All patients have an aortic stenosis (AS) diagnostic label (none, early AS, or significant AS; for more see our severity diagnosis label primer)
- Some images from each study have view label annotations (one of PLAX/PSAX/A2C/A4C/other, for more see our view label primer)
- We partition these by patient into different “splits” of 360 training / 119 validation / 120 test studies.
view_labeled_set: 705 studies from 703 unique patients- These studies have view labels, but no AS diagnosis labels
unlabeled_set: 5486 studies from 5287 patients- No labels are available for any studies in this set
This TMED-2 dataset is referred to in some of our manuscripts as the DEV479 dataset, because models are trained on development set of 479 studies (360 for train and 119 for validation). The heldout test set contains data 120 studies.
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Summary Table
Summary statistics of TMED-2 dataset
| Dataset | Num. Patients | Num. Studies | Num. Labeled Images | Num. Unlabeled Images |
|---|---|---|---|---|
| fully labeled set | 577 | 599 | 17270 | 26596 |
| partially labeled set | 703 | 705 | 7694 | 37576 |
| unlabeled set | 5287 | 5486 | 0 | 353500 |
Image preprocessing
Every image in this dataset is a 2D TTE image stored at 112x112 pixel resolution in PNG format.
In TMED-2, we used metadata available in the raw DICOM files to ensure only the 2D TTE images from each study are included (filtering out doppler images, m-mode images, and colorflow images). Note that this is more aggressive preprocessing than in TMED-1 (where we did some filtering by aspect ratio, but this may have not discarded all doppler images, m-mode images, or colorflow images).