Lab Members

J. Kwon, H. Lee, S. Cho, C.-S. Chung, M. J. Lee#, and H. Park#, “Machine learning-based automated classification of headache disorders using patient-reported questionnaires”, Scientific Reports, vol. 10,  August 2020

J. H. Ahn*, J. Kwon*, J. H. Won, K. Byeon, J. Youn, H. Park#, and J. W. Cho#, “Waiting Impulsivity in Progressive Supranuclear Palsy-Richardson’s Syndrome”, Frontiers in Neuroscience, vol. 17, article 1240709, doi: /10.3389/fnins.2023.1240709, September 2023

J. Kwon, S. W. Seo#, H. Park#, “Anatomically-Guided Segmentation of Cerebral Microbleeds in T1-weighted and T2*-weighted MRI”, accepted for Medical image computing and computer-assisted intervention (MICCAI) 2024, June 2024.

J. Kwon, J. Kim, H. Park#, “Leveraging Segmentation-Guided Spatial Feature Embedding for Overall Survival Prediction in Glioblastoma with Multimodal Magnetic Resonance Imaging”, accepted for Computer Methods and Programs in Biomedicine, July 2024.

J. Kwon, S. W. Seo, H. Park#, “Enhancing Cerebral Microbleed Segmentation with Pretrained UNETR++”, accepted for Bioinformatics and Biomedicine (BIBM) 2024, October 2024. 

J. Lee*, S. Kim*, S. Park, H. Choi, B. Park#, H. Park#, “Atypical maturation of the functional connectome hierarchy in autism”, accepted for Molecular Autism, January 2025.

J. Lee, K. Byeon, S. Kim, B. Park, H. Park#, “Revealing the multivariate associations between autistic traits and principal functional connectome”, accepted for Neuroinformatics, February 2025.

I. Na*, J. Noh*, C. K. Kim#, J.-W. Lee#, H. Park#, “Combined radiomics-clinical model to predict platinum-sensitivity in advanced high-grade serous ovarian carcinoma using multimodal MRI”, vol. 14, article 1341228, doi: 10.3389/fonc.2024.1341228, Frontiers in Oncology, January 2024.

I. Na, J. Kim, E. S. Ko, H. Park#,, “RadiomicsFill-Mammo: Synthetic Mammogram Mass Manipulation with Radiomics Features”, accepted for Medical image computing and computer-assisted intervention (MICCAI) 2024, June 2024.

J. Kim and H. Park#, “Adaptive Latent Diffusion Model for 3D Medical Image to Image Translation: Multi-modal Magnetic Resonance Imaging Study”, Winter Conference on Applications of Computer Vision (WACV), p. 7604-7613, January 2024.

J. Kim*, M. Kim*, H. Park#, “Domain Aware Multi-Task Pretraining of 3D Swin Transformer for T1-weighted Brain MRI”, accepted for Asian Conference on Computer Vision (ACCV) 2024, September 2024.

J. Kim, I. Na, E. S. Ko, H. Park#, “Tumor Synthesis conditioned on Radiomics”, accepted for Winter Conference on Applications of Computer Vision (WACV), October 2024.

H. Choi*, K. Byeon*, B. Park, J. Lee, S. L. Valk, B. Bernhardt, A. D. Martino, M. Milham, S.-J. Hong#, and H. Park#, “Diagnosis-informed connectivity subtyping discovers subgroups of autism with reproducible symptom profiles”, accepted for Neuroimage, April 2022.

H. Choi, K. Byeon, J. Lee. S. Hong, B. Park#, H. Park#, “Identifying subgroups of eating behavior traits unrelated to obesity using functional connectivity and feature representation learning”, accepted for Human Brain Mapping, December 2023

H. Choi*, Y. Cho*, C. Min, K. Nam, E. Kim, S. Lee, J. Kim#, "Multiclassification of the symptom severity of social anxiety disorder using digital phenotypes and feature representation learning", Digitial Health, accepted May 2024

J. Chung, S. Kim, J. H. Won#, H. Park#, “Integrating Multimodal Neuroimaging and Genetics: A Structurally-Linked Sparse Canonical Correlation Analysis Approach”, accepted for IEEE Journal of Translational Engineering in Health & Medicine, September 2024.

S. Ra, J. Kim, I. Na, E. S. Ko, and H. Park#, “Enhancing Radiomics Features via a Large Language Model for Classifying Benign and Malignant Breast Tumors in Mammography”, accepted for Computer Methods and Programs in Biomedicine, April 2025

S. Oh*, S. Kim*, J. Lee, B. Park, J. H. Won, H. Park#, “Multimodal Analysis of Disease Onset in Alzheimer’s Disease Using Connectome, Molecular, and Genetics Data”, accepted for NeuroImage: Clinical, August 2024.

G. Jo, J. Kim, B. Park, H. Park#, “DeAFusion: Detail-Aware Image Fusion for Whitematter Hyperintensity Segmentation”, accepted for Bioinformatics and Biomedicine (BIBM) 2024, October 2024.