Asymmetric 3D Context Fusion for Universal Lesion Detection
Jiancheng Yang,
Yi He,
Kaiming Kuang
et al.
Abstract:Modeling 3D context is essential for high-performance 3D medical image analysis. Although 2D networks benefit from large-scale 2D supervised pretraining, it is weak in capturing 3D context. 3D networks are strong in 3D context yet lack supervised pretraining. As an emerging technique, 3D context fusion operator, which enables conversion from 2D pretrained networks, leverages the advantages of both and has achieved great success. Existing 3D context fusion operators are designed to be spatially symmetric, i.e.,… Show more
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