Video-level medical image annotation

Abstract

Techniques for training models, using video-level annotations as additional supervision, to generate both video-level and frame-level predictions based on medical images are disclosed. In some examples, medical imaging data is received including frame-level annotations and video-level annotations. A training dataset may be generated comprising frame-level ground truth data and video-level ground truth data, and the model is trained, using the training dataset, to generate frame-level feature localizations/segmentations and/or video-level feature predictions on new medical imaging data. In some examples, a model includes a frame-to-video feature encoder that learns to generate video-level predictions from frame-level predictions. The frame-to-video feature encoder may be jointly trained based on video-level annotations along with frame-level annotations during training.

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