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Spiral Contrastive Learning: An Efficient 3D Representation Learning Method for Unannotated CT Lesions
In the past five years, several works have tailored for unsupervised representations of CT lesions via two-dimensional (2D) and three-dimensional (3D) self-supervised learning (SSL) algorithms.
MVCNet: Multiview Contrastive Network for Unsupervised Representation Learning for 3D CT Lesions
To avoid the subjectivity associated with these methods, we propose the MVCNet, a novel unsupervised three dimensional (3D) representation learning method working in a transformation-free manner.
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