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CAiD: Context-Aware Instance Discrimination for Self-supervised Learning in Medical Imaging. (arXiv:2204.07344v1 [eess.IV])
cs.CV updates on arXiv.org arxiv.org
Recently, self-supervised instance discrimination methods have achieved
significant success in learning visual representations from unlabeled
photographic images. However, given the marked differences between photographic
and medical images, the efficacy of instance-based objectives, focusing on
learning the most discriminative global features in the image (i.e., wheels in
bicycle), remains unknown in medical imaging. Our preliminary analysis showed
that high global similarity of medical images in terms of anatomy hampers
instance discrimination methods for capturing a set of distinct features,
negatively impacting …
arxiv context discrimination imaging learning medical medical imaging self-supervised learning supervised learning