Top-tier AI Conferences

  Conference lists: ECCV, ICLR, MICCAI, NeurIPS, etc.

1. Boah Kim*, Yujin Oh*, and Jong Chul Ye, “Diffusion Adversarial Representation Learning for Self-supervised Vessel Segmentation”, International Conference on Learning Representations (ICLR), May 2023 (* Co-first authors)

2. Boah Kim, Inhwa Han, and Jong Chul Ye, “DiffuseMorph: Unsupervised Deformable Image Registration Using Diffusion Model”, European Conference on Computer Vision (ECCV), Oct 2022

3. Boah Kim and Jong Chul Ye, “Diffusion Deformable Model for 4D Temporal Medical Image Generation”, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Sep 2022 (Provisional accept)

4. Sangjoon Park*, Gwanghyun Kim*, Jeongsol Kim, Boah Kim, and Jong Chul Ye, “Federated Split Task-Agnostic Vision Transformer for COVID-19 CXR Diagnosis”, Advances in Neural Information Processing Systems (NeurIPS), Dec 2021 (* Co-first authors)

5. Boah Kim, Jieun Kim, June-Goo Lee, Dong Hwan Kim, Seong Ho Park, and Jong Chul Ye, “Unsupervised Deformable Image Registration using Cycle-consistent CNN”, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Oct 2019

Other Conferences

International conference lists:  ISBI, SIIM, SPIE, CMIMI, etc.

Domestic conference lists:  KoSAIM, IPIU, etc.

1. Tejas Sudharshan Mathai*, Boah Kim*, Praveen Thoppey Srinivasan Balamuralikrishna, and Ronald M. Summers, “Capability of Multi-Modal Large Language Models for Matching Findings in Longitudinal CT Studies”, Society for Imaging Informatics in Medicine (SIIM), May 2025 (* Co-first authors)

2. Boah Kim*, Tejas Sudharshan Mathai*, Oana M. Stroie, and Ronald M. Summers, “Capability of a Privacy-Preserving LLAMA-2 Language Model for Tracking Matched Findings in Follow-up Reports”, Society for Imaging Informatics in Medicine (SIIM), Jun 2024 (* Co-first authors)

3. Boah Kim, Tejas Sudharshan Mathai, Kimberly Helm, and Ronald M. Summers, “Automated Classification of Multi-parametric Body MRI Series”, IEEE International Symposium on Biomedical Imaging (ISBI), May 2024

4. Boah Kim, Tejas Sudharshan Mathai, and Ronald M. Summers, “Unsupervised Multi-parametric MRI Registraiton Using Neural Optimal Transport”, Proceedings of SPIE, Medical Imaging 2024: Computer-Aided Diagnosis (SPIE, MI-CAD), Feb 2024

5. Kimberly Helm, Tejas Sudharshan Mathai, Boah Kim, and Ronald M. Summers, “Automated Classification of Body MRI Sequence Type Using Convolutional Neural Networks”, Proceedings of SPIE, Medical Imaging 2024: Computer-Aided Diagnosis (SPIE, MI-CAD), Feb 2024

6. Boah Kim, Tejas Sudharshan Mathai, Ronald M. Summers, “Deformable Multi-modal Image Registration via Neural Optimal Transport: An Application to Multi-parametric MRI Registration”, Conference on Machine Intelligence in Medical Imaging (CMIMI), Oct 2023

7. Yan Zhuang, Benjamin Hou, Tejas Sudharshan Mathai, Pritam Mukherjee, Boah Kim, Ronald M. Summers, “Semantic Image Synthesis for Abdominal CT”, Deep Generative Models for Medical Image Computing and Computer Assisted Intervention (DGM4MICCAI), Oct 2023

8. Boah Kim, Inhwa Han, and Jong Chul Ye, “Diffusion-based Unsupervised Medical Image Registration Model”, Korean Society of Artificial Intelligence in Medicine (KoSAIM), Oct 2022

9. Inhwa Han, Boah Kim, Eung Yeop Kim, and Jong Chul Ye, “Contrast Agent Removal for Brain CT Angiography Using Switchable CycleGAN with AdaIN and Histogram Equalization”, IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), Jun 2022

10. Boah Kim, Eung Yeop Kim, and Jong Chul Ye, “Medical Image Synthesis with Improved Cycle-GAN: CT from CECT”, IEEE International Symposium on Biomedical Imaging (ISBI) Workshop on Deep Learning for Biomedical Image Reconstruction, Apr 2020

11. Boah Kim*, Junyoung Kim*, Wontaek Seo, Choul Woo Shin, and Jong Chul Ye, “Multi-energy Bone Subtraction in Chest Radiography by Eigenvalue Decomposition”, IEEE International Symposium on Biomedical Imaging (ISBI) Workshop on Deep Learning for Biomedical Image Reconstruction, Apr 2020 (* Co-first authors)

12. Boah Kim and Jong Chul Ye, “Brain Tumor Segmentation Using Cycle-Consistent Adversarial Network”, International Society for Magnetic Resonance in Medicine (ISMRM) Workshop on Machine Learning, Mar 2018

13. Boah Kim and Jong Chul Ye, “Liver Lesion Segmentation of Computed Tomography Images by Learning Convolutional Neural Network”, Domestic Workshop on Image Processing and Image Understanding (IPIU), Feb 2018