Keun-Soo Heo

I am a Ph.D. candidate at the Medical Artificial Intelligence Lab. (MAILab) in the Department of Artificial Intelligence in Korea University, South Korea.

I'm interested in Deep Learning, Multi-Modal, Medical AI, and Generative Models.

In 2020, I completed my Bachelor of Science in the Department of Information, Communication and Electronic Engineering at The Catholic University of Korea.

From 2017 to 2020, I worked as an undergraduate researcher at the Image Signal Processing Lab. at The Catholic University of Korea.

Email / Scholar / Linkdein / Github

International Publication

	PAPER Keun-Soo Heo et al. Provisionally Accepted (Top 9% Paper) International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2025
	Group-wise Compression and Summarization via LLM-based Ensemble for Chest X-ray Report Generation Oral Presentation Sang-Jun Park, Keun-Soo Heo, Bogyeong Kang, Minjoo Lim, WooHyeok Choi, and Tae-Eui Kam IEEE Engineering in Medicine and Biology Society (EMBC), 2025
	DART: Disease-aware Image-Text Alignment and Self-correcting Re-alignment for Trustworthy Radiology Report Generation Sang-Jun Park, Keun-Soo Heo*, Dong-Hee Shin, Young-Han Son, Ji-Hye Oh, and Tae-Eui Kam Equal contribution IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025
	Target-Aware Cross-Modality Unsupervised Domain Adaptation for Vestibular Schwannoma and Cochlea Segmentation Bogyeong Kang, Hyeonyeong Nam, Myeongkyun Kang, Keun-Soo Heo, Minjoo Lim, Ji-Hye Oh, and Tae-Eui Kam Scientific Reports, 2024
	A Learnable Continuous Wavelet-based Multi-Branch Attentive Convolutional Neural Network for Spatio-Spectral-Temporal EEG Signal Decoding Jun-Mo Kim, Keun-Soo Heo, Dong-Hee Shin, Hyeonyeong Nam, Dong-Ok Won, Ji-Hoon Jeong, and Tae-Eui Kam Expert Systems With Applications, 2024
	Enhanced Structure Preservation and Multi-View Approach in Unsupervised Domain Adaptation for Optic Disc and Cup Segmentation Sanghyeon Cho, Bogyeong Kang, Keun-Soo Heo, Eunjung Jo, and Tae-Eui Kam IEEE International Symposium on Biomedical Imaging (ISBI), 2024
	A Unified Multi-Modality Fusion Framework for Deep Spatio-Temporal-Spectral Feature Learning in Resting-State fMRI Denoising Minjoo Lim, Keun-Soo Heo, Jun-mo Kim, Bogyeong Kang, Weili Lin, Han Zhang, Dinggang Shen, and Tae-Eui Kam IEEE Journal of Biomedical and Health Informatics, 2024
	Multi-view Cross-Modality MR Image Translation for Vestibular Schwannoma and Cochlea Segmentation Bogyeong Kang, Hyeonyeong Nam, Ji-Wung Han, Keun-Soo Heo, Tae-Eui Kam MICCAI BrainLes Workshop, 2022
	Deep Attentive Spatio-Temporal Feature Learning for Automatic Resting-State fMRI Denoising Keun-Soo Heo, Dong-Hee Shin, Sheng-Che Hung, Weili Lin, Han Zhang, Dinggang Shen, Tae-Eui Kam NeuroImage, 2022 github

Domestic Publication

Efficient Deep Neural Network for Restoring Image Intensity
Keun-Soo Heo, Yunju Kim, Changwoo Lee
IEIE Transactions on Smart Processing & Computing, 2019
github