A new public coronary-angiography benchmark finds ConvNeXt V2 + DeepLabV3+ is the best single model (macro F1 = 0.456), with a three-model ensemble reaching 0.479.
Auto- matic segmentation of coronary arteries in X-Ray angiograms using multiscale anal- ysis and artificial neural networks,
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CARDIAG: A Dense Segment Classification Benchmark of Deep Learning Architectures for Coronary Angiography
A new public coronary-angiography benchmark finds ConvNeXt V2 + DeepLabV3+ is the best single model (macro F1 = 0.456), with a three-model ensemble reaching 0.479.