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Boah Kim

3 accepted papers

2023

Diffusion Adversarial Representation Learning for Self-supervised Vessel Segmentation

ICLR 2023poster

Vessel segmentation in medical images is one of the important tasks in the diagnosis of vascular diseases and therapy planning. Although learning-based segmentation approaches have been extensively studied, a large amount of ground-truth labels are required in supervised methods and confusing backgr…

Cited by 85SourcePDFScholar
2022

DiffuseMorph: Unsupervised Deformable Image Registration Using Diffusion Model

ECCV 2022poster

"Deformable image registration is one of the fundamental tasks in medical imaging. Classical registration algorithms usually require a high computational cost for iterative optimizations. Although deep-learning-based methods have been developed for fast image registration, it is still challenging to…

Cited by 98SourcePDFScholar
2021

Federated Split Task-Agnostic Vision Transformer for COVID-19 CXR Diagnosis

NeurIPS 2021poster

Federated learning, which shares the weights of the neural network across clients, is gaining attention in the healthcare sector as it enables training on a large corpus of decentralized data while maintaining data privacy. For example, this enables neural network training for COVID-19 diagnosis on…

Cited by 54SourcePDFScholar