Boah Kim

Orcid: 0000-0001-6178-9357

According to our database1, Boah Kim authored at least 15 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
C-DARL: Contrastive diffusion adversarial representation learning for label-free blood vessel segmentation.
Medical Image Anal., January, 2024

Automated Classification of Body MRI Sequence Type Using Convolutional Neural Networks.
CoRR, 2024

2023
Task-Agnostic Vision Transformer for Distributed Learning of Image Processing.
IEEE Trans. Image Process., 2023

Semantic Image Synthesis for Abdominal CT.
Proceedings of the Deep Generative Models - Third MICCAI Workshop, 2023

Diffusion Adversarial Representation Learning for Self-supervised Vessel Segmentation.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Diffusion Deformable Model for 4D Temporal Medical Image Generation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

DiffuseMorph: Unsupervised Deformable Image Registration Using Diffusion Model.
Proceedings of the Computer Vision - ECCV 2022, 2022

Contrast Agent Removal for Brain CT Angiography Using Switchable CycleGAN with AdaIN and Histogram Equalization.
Proceedings of the 4th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2022

2021
CycleMorph: Cycle consistent unsupervised deformable image registration.
Medical Image Anal., 2021

DiffuseMorph: Unsupervised Deformable Image Registration Along Continuous Trajectory Using Diffusion Models.
CoRR, 2021

Federated Split Vision Transformer for COVID-19 CXR Diagnosis using Task-Agnostic Training.
CoRR, 2021

Federated Split Task-Agnostic Vision Transformer for COVID-19 CXR Diagnosis.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Mumford-Shah Loss Functional for Image Segmentation With Deep Learning.
IEEE Trans. Image Process., 2020

2019
Multiphase Level-Set Loss for Semi-Supervised and Unsupervised Segmentation with Deep Learning.
CoRR, 2019

Unsupervised Deformable Image Registration Using Cycle-Consistent CNN.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019


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