publication

PLATYPUS: Progressive Local Surface Estimator for Arbitrary-Scale Point Cloud Upsampling

#Point Cloud Upsampling   #3D Point Cloud  

Donghyun Kim, Hyeonkyeong Kwon, Yumin Kim, Seong Jae Hwang

Association for the Advancement of Artificial Intelligence (AAAI), 2025.

[arxiv]

Deep Learning-Based Pre-contrast CT Parcellation for MRI-Free Brain Amyloid PET Quantification 

#PET   #CT   #Medical Imaging   #Whole-brain Segmentation

Kyobin Choo, Jaehoon Joo, Sangwon Lee, Daesung Kim, Hyunkeong Lim, Dongwoo Kim, Seongjin Kang, Seong Jae Hwang*, Mijin Yun*

Clinical Nuclear Medicine, 2024. [Impact Factor: 10.0]

Disentangling Disentangled Representations: Towards Improved Latent Units via Diffusion Models

#Disentanglement   #Diffusion Model 

Youngjun Jun, Jiwoo Park, Kyobin Choo, Tae Eun Choi, Seong Jae Hwang

Winter Conference on Applications of Computer Vision (WACV), 2025.

[arxiv]

DragText: Rethinking Text Embedding in Point-based Image Editing 

#Image Editing   #Diffusion Model 

Gayoon Choi, Taejin Jeong, Sujung Hong, Jaehoon Joo, Seong Jae Hwang

Winter Conference on Applications of Computer Vision (WACV), 2025. [Round 1 Accept (12% of round 1 submissions)]

[Project Page] [arxiv]

Distilling Spectral Graph for Object-Context Aware Open-Vocabulary Semantic Segmentation

#Open-Vocabulary Semantic Segmentation   #Spectral Method  

Chanyoung Kim, Dayun Ju, Woojung Han, Ming-Hsuan Yang, Seong Jae Hwang

[Project Page] [arxiv]

EAGLE: Eigen Aggregation Learning for Object-Centric Unsupervised Semantic Segmentation

#Object-centric Learning   #Segmentation  

Chanyoung Kim*, Woojung Han*, Dayun Ju, Seong Jae Hwang

Computer Vision and Pattern Recognition (CVPR), 2024. [Highlight (top 2.8% of submissions)]

[Project Page] [open access] [arxiv] [github]

Advancing Text-Driven Chest X-Ray Generation with Policy-Based Reinforcement Learning 

#Diffusion Model   #Text-to-Image Generation   #Reinforcement Learning   #Medical Imaging 

Woojung Han*, Chanyoung Kim*, Dayun Ju, Yumin Shim, Seong Jae Hwang

Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024. [Spotlight (top 3.4% of submissions)]

[Project Page] [arxiv] [github] 

Slice-Consistent 3D Volumetric Brain CT-to-MRI Translation with 2D Brownian Bridge Diffusion Model 

#Diffusion Model   #Image Translation   #Medical Imaging 

Kyobin Choo, Youngjun Jun, Mijin Yun, Seong Jae Hwang

Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024. [Early Accept (top 11% of submissions)]

[Project Page] [arxiv] [github]

Parameter Efficient Fine Tuning for Multi-scanner PET to PET Reconstruction

#PEFT   #PET Reconstruction   #Medical Imaging 

Yumin Kim*, Gayoon Choi*, Seong Jae Hwang

Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024.

[Project Page] [arxiv] [github]

ESPA: An Unsupervised Harmonization Framework via Enhanced Structural Preserving Augmentation

#Data Harmonization   #Medical Imaging 

Mahbaneh Eshghzadeh Torbati, Davneet S. Minhas, Ahmad Tafti, Charles S. DeCarli, Dana L. Tudorascu, Seong Jae Hwang

Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024.

[PDF]

Complementary Branch Fusing Class and Semantic Knowledge for Robust Weakly Supervised Semantic Segmentation 

#Semantic Segmentation   #Weakly Supervised Learning 

Woojung Han, Seil Kang, Kyobin Choo, Seong Jae Hwang

Pattern Recognition, 2024. [Impact Factor: 7.5]

[elsevier] [arxiv]

Superpixel-ComBat Modeling: A Joint Approach for Harmonization and Characterization of Inter-Scanner Variability in T1-Weighted Images

#Data Harmonization   #Medical Imaging 

Chang-Le Chen, Mahbaneh Eshaghzadeh Torbati, Davneet S. Minhas, Charles M. Laymon, Seong Jae Hwang, Murat Bilgel, Adina Crainiceanu, Hecheng Jin, Weiquan Luo, Pauline Maillard, Evan Fletcher, Ciprian M. Crainiceanu, Charles S. DeCarli, Howard J. Aizenstein, Dana L. Tudorascu

Imaging Neuroscience, 2024.

[MIT Press]

FALCON: Frequency Adjoint Link with CONtinuous Density Mask for Fast Single Image Dehazing

#Dehazing   #Image Restoration   

Donghyun Kim, Seil Kang, Seong Jae Hwang

arXiv, 2024.

[arxiv]

WoLF: Large Language Model Framework for CXR Understanding 

#LLM   #Vision-Language Model   #Medical Imaging 

Seil Kang, Donghyun Kim, Junhyeok Kim, Hyo Kyung Lee, Seong Jae Hwang

arXiv, 2024.

[arxiv]

Brain-Streams: fMRI-to-Image Reconstruction with Multi-modal Guidance

#Image Reconstruction   #Vision-Language Model   #Medical Imaging 

Jaehoon Joo, Taejin Jeong, Seong Jae Hwang

arXiv, 2024.

[arxiv]

MISPEL: A supervised deep learning method for harmonizing multi-scanner neuroimaging data

#Data Harmonization   #Medical Imaging  

Mahbaneh Eshghzadeh Torbati, Davneet S. Minhas, Charles M. Laymon, Pauline Maillard, James D. Wilson, Chang-Le Chen, Ciprian M. Crainiceanu, Charles S. DeCarli, Seong Jae Hwang, Dana L. Tudorascu

Medical Image Analysis (MIA), 2023. [Impact Factor: 13.828, JCR 1.2%]

[MIA]

Domain Adversarial Neural Networks for Domain Generalization: When It Works and How to Improve

#Domain Generalization 

Anthony Sicilia, Xingchen Zhao, Seong Jae Hwang

Machine Learning, 2023. [Impact Factor: 7.5]

[Machine Learning][arxiv]

Evidence-empowered Transfer Learning for Alzheimer's Disease

#Transfer Learning   #Medical Imaging  

Kai Ong, Hana Kim, Minjin Kim, Jinseong Jang, Beomseok Sohn, Yoon Seong Choi, Dosik Hwang, Seong Jae Hwang, Jinyoung Yeo

IEEE International Symposium on Biomedical Imaging (ISBI), 2023.

[arxiv]

PAC-Bayesian Domain Adaptation Bounds for Multiclass Learners

#PAC-Bayesian Learning   #Domain Adaptation  

Anthony Sicilia, Katherine Atwell, Malihe Alikhani, Seong Jae Hwang

Conference on Uncertainty in Artificial Intelligence (UAI), 2022. [Best Paper Award (1 of 712 submitted papers)]

[UAI][arxiv][github]

Test-time Fourier Style Calibration for Domain Generalization

#Domain Generalization 

Xingchen Zhao, Chang Liu, Anthony Sicilia, Seong Jae Hwang, Yun Fu

International Joint Conference on Artificial Intelligence (IJCAI), 2022.

[IJCAI][arxiv]

The Change that Matters in Discourse Parsing: Estimating the Impact of Domain Shift on Parser Error

#NLP   #Domain Adaptation  

Katherine Atwell, Anthony Sicilia, Seong Jae Hwang, Malihe Alikhani

Findings of ACL, 2022.

[Findings][arxiv][github]

Anatomic development of the upper airway during the first five years of life: A three-dimensional imaging study

#Medical Imaging  

Ying Ji Chuang, Seong Jae Hwang, Kevin A Buhr, Courtney A Miller, Gregory D Avey, Brad H Story, Houri K. Vorperian

PLOS ONE, 2022.

[PLOS ONE]

A multi-scanner neuroimaging data harmonization using RAVEL and ComBat

#Data Harmonization   #Medical Imaging  

Mahbaneh Eshghzadeh Torbati, Davneet S. Minhas, Ghasan Ahmad, Erin E. O'Connor, John Muschelli, Charles Laymon, Zixi Yang, Annie Cohen, Howard J. Aizenstein, William E. Klunk, Bradley T. Christian, Seong Jae Hwang, Ciprian M. Crainiceanu, Dana L. Tudorascu

NeuroImage, 2021.

[NeuroImage]

Multi-scanner Harmonization of Paired Neuroimaging Data via Structure Preserving Embedding Learning

#Data Harmonization   #Medical Imaging  

Mahbaneh Eshghzadeh Torbati, Dana L. Tudorascu, Pauline Maillard, Davneet S. Minhas, Charles S. DeCarli, Seong Jae Hwang

The First Workshop on Computer Vision for Automated Medical Diagnosis (CVAMD), International Conference on Computer Vision (W-ICCV), 2021. [Oral]

[W-ICCV] [github]

Point Cloud Augmentation with Weighted Local Transformations

#Point Cloud 

Sihyeon Kim, Sanghyeok Lee, Dasol Hwang, Jaewon Lee, Seong Jae Hwang, Hyunwoo Kim

International Conference on Computer Vision (ICCV), 2021.

[ICCV] [github]

PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging

#PAC-Bayesian Learning   #Medical Imaging  

Anthony Sicilia, Xingchen Zhao, Anastasia Sosnovskikh, Seong Jae Hwang

Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021.

[MICCAI] [arxiv] [github]

Cycle Consistent Embedding of 3D Brains with Auto-Encoding Generative Adversarial Networks

#GAN   #Medical Imaging  

Shibo Xing, Harsh Sinha, Seong Jae Hwang

Medical Imaging with Deep Learning (Short Paper - MIDL), 2021.

[openreview] [github]

Learning Multi-resolution Graph Edge Embedding for Discovering Brain Network Dysfunction in Neurological Disorders

#GCN   #Medical Imaging  

Xin Ma, Guorong Wu, Seong Jae Hwang, Won Hwa Kim

Information Processing in Medical Imaging (IPMI), 2021. [Acceptance rate: 30.0%]

[IPMI]

Multi-Domain Learning by Meta-Learning: Taking Optimal Steps in Multi-Domain Loss Landscapes by Inner-Loop Learning

#Meta-learning   #Medical Imaging  

Anthony Sicilia, Xingchen Zhao, Davneet Minhas, Erin O'Connor, Howard Aizenstein, William Klunk, Dana Tudorascu, Seong Jae Hwang

IEEE International Symposium on Biomedical Imaging (ISBI), 2021.

[ISBI 2021] [arxiv] [github]

Robust White Matter Hyperintensity Segmentation on Unseen Domain

#Domain Generalization   #Segmentation  #Medical Imaging  

Xingchen Zhao, Anthony Sicilia, Davneet Minhas, Erin O'Connor, Howard Aizenstein, William Klunk, Dana Tudorascu, Seong Jae Hwang

IEEE International Symposium on Biomedical Imaging (ISBI), 2021.

[ISBI 2021] [arxiv] [github]