Fast multiscale vessel enhancement filtering. - Dong Hye Ye; Dongjin Kwon; Il Dong Yun; Sang Uk Lee (Image Processing, 2008)

Groupwise morphometric analysis based on high dimensional clustering. - Dong Hye Ye; Kilian M. Pohl; Harold Litt; Christos Davatzikos (CVPR Workshops, 2010)

GRAM: A framework for geodesic registration on anatomical manifolds. - Jihun Hamm; Dong Hye Ye; Ragini Verma; Christos Davatzikos (Medical Image Anal., 2010)

Morphological Classification: Application to Cardiac MRI of Tetralogy of Fallot. - Dong Hye Ye; Harold Litt; Christos Davatzikos; Kilian M. Pohl (FIMH, 2011)

Disease classification and prediction via semi-supervised dimensionality reduction. - Kayhan N. Batmanghelich; Dong Hye Ye; Kilian M. Pohl; Ben Taskar; Christos Davatzikos (ISBI, 2011)

Semi-supervised Pattern Classification: Application to Structural MRI of Alzheimer's Disease. - Dong Hye Ye; Kilian M. Pohl; Christos Davatzikos (PRNI, 2011)

Combining regional metrics for disease-related brain population analysis. - Dong Hye Ye; Jihun Hamm; Kilian M. Pohl (ISBI, 2012)

Regional Manifold Learning for Deformable Registration of Brain MR Images. - Dong Hye Ye; Jihun Hamm; Dongjin Kwon; Christos Davatzikos; Kilian M. Pohl (MICCAI (3), 2012)

Validation of DRAMMS among 12 Popular Methods in Cross-Subject Cardiac MRI Registration. - Yangming Ou; Dong Hye Ye; Kilian M. Pohl; Christos Davatzikos (WBIR, 2012)

Discriminative Segmentation-Based Evaluation Through Shape Dissimilarity. - Ender Konukoglu; Ben Glocker; Dong Hye Ye; Antonio Criminisi; Kilian M. Pohl (IEEE Trans. Medical Imaging, 2012)

FLOOR: Fusing Locally Optimal Registrations. - Dong Hye Ye; Jihun Hamm; Benoit Desjardins; Kilian M. Pohl (MICCAI (3), 2013)

Modality Propagation: Coherent Synthesis of Subject-Specific Scans with Data-Driven Regularization. - Dong Hye Ye; Darko Zikic; Ben Glocker; Antonio Criminisi; Ender Konukoglu (MICCAI (1), 2013)

Auto-encoding of discriminating morphometry from cardiac MRI. - Dong Hye Ye; Benoit Desjardins; Victor Ferrari; Dimitris N. Metaxas; Kilian M. Pohl (ISBI, 2014)

Regional Manifold Learning for Disease Classification. - Dong Hye Ye; Benoit Desjardins; Jihun Hamm; Harold Litt; Kilian M. Pohl (IEEE Trans. Medical Imaging, 2014)

Joint metal artifact reduction and segmentation of CT images using dictionary-based image prior and continuous-relaxed potts model. - Pengchong Jin; Dong Hye Ye; Charles A. Bouman (ICIP, 2015)

The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS). - Bjoern H. Menze; András Jakab; Stefan Bauer; Jayashree Kalpathy-Cramer; Keyvan Farahani; Justin S. Kirby; Yuliya Burren; Nicole Porz; Johannes Slotboom; Roland Wiest; Levente Lanczi; Elizabeth R. Gerstner; et al. (IEEE Trans. Medical Imaging, 2015)

A Supervised Learning Approach for Dynamic Sampling. - G. M. Dilshan Godaliyadda; Dong Hye Ye; Michael D. Uchic; Michael A. Groeber; Gregery T. Buzzard; Charles A. Bouman (Computational Imaging, 2016)

Multi-target detection and tracking from a single camera in Unmanned Aerial Vehicles (UAVs). - Jing Li; Dong Hye Ye; Timothy H. Chung; Mathias Kölsch; Juan P. Wachs; Charles A. Bouman (IROS, 2016)

A Gaussian Mixture MRF for Model-Based Iterative Reconstruction With Applications to Low-Dose X-Ray CT. - Ruoqiao Zhang; Dong Hye Ye; Debashish Pal; Jean-Baptiste Thibault; Ken D. Sauer; Charles A. Bouman (IEEE Trans. Computational Imaging, 2016)

A Model Based Neuron Detection Approach using Sparse Location Priors. - Soumendu Majee; Dong Hye Ye; Gregery T. Buzzard; Charles A. Bouman (Computational Imaging, 2017)

Synchrotron X-Ray Diffraction Dynamic Sampling for Protein Crystal Centering. - Nicole M. Scarborough; G. M. Dilshan P. Godaliyadda; Dong Hye Ye; David J. Kissick; Shijie Zhang; Justin A. Newman; Michael J. Sheedlo; Azhad Chowdhury; Robert F. Fischetti; Chittaranjan Das; Gregery T. Buzzard; Charles A. Bouman; et al. (Computational Imaging, 2017)

A Framework for Dynamic Image Sampling Based on Supervised Learning (SLADS). - G. M. Dilshan P. Godaliyadda; Dong Hye Ye; Michael D. Uchic; Michael A. Groeber; Gregery T. Buzzard; Charles A. Bouman (CoRR, 2017)

2.5D Deep Learning For CT Image Reconstruction Using A Multi-GPU Implementation. - Amirkoushyar Ziabari; Dong Hye Ye; Somesh Srivastava; Ken D. Sauer; Jean-Baptiste Thibault; Charles A. Bouman (ACSSC, 2018)

A Supervised Learning Approach for Dynamic Sampling (SLADS) in Raman Hyperspectral Imaging. - Shijie Zhang; Zhengtian Song; G. M. Dilshan P. Godaliyadda; Dong Hye Ye; Atanu Sengupta; Gregery T. Buzzard; Charles A. Bouman; Garth J. Simpson (Computational Imaging, 2018)

Deep Learning for Moving Object Detection and Tracking from a Single Camera in Unmanned Aerial Vehicles (UAVs). - Dong Hye Ye; Jing Li; Qiulin Chen; Juan P. Wachs; Charles A. Bouman (IMAWM, 2018)

Deep Back Projection for Sparse-View CT Reconstruction. - Dong Hye Ye; Gregery T. Buzzard; Max Ruby; Charles A. Bouman (GlobalSIP, 2018)

Deep Residual Learning for Model-Based Iterative CT Reconstruction Using Plug-and-Play Framework. - Dong Hye Ye; Somesh Srivastava; Jean-Baptiste Thibault; Ken D. Sauer; Charles A. Bouman (ICASSP, 2018)

A Framework for Dynamic Image Sampling Based on Supervised Learning. - G. M. Dilshan P. Godaliyadda; Dong Hye Ye; Michael D. Uchic; Michael A. Groeber; Gregery T. Buzzard; Charles A. Bouman (IEEE Trans. Computational Imaging, 2018)

Multi-target tracking with an event-based vision sensor and a partial-update GMPHD filter. - Benjamin J. Foster; Dong Hye Ye; Charles A. Bouman (Computational Imaging, 2019)

The human body at cellular resolution: the NIH Human Biomolecular Atlas Program. - Michael P. Snyder; Shin Lin; Amanda Posgai; Mark Atkinson; Aviv Regev; Jennifer Rood; Orit Rozenblatt-Rosen; Leslie Gaffney; Anna Hupalowska; Rahul Satija; Nils Gehlenborg; Jay Shendure; et al. (Nat., 2019)

Prior-Guided Metal Artifact Reduction for Iterative X-Ray Computed Tomography. - Zhiqian Chang; Dong Hye Ye; Somesh Srivastava; Jean-Baptiste Thibault; Ken D. Sauer; Charles A. Bouman (IEEE Trans. Medical Imaging, 2019)

Age-Conditioned Synthesis of Pediatric Computed Tomography with Auxiliary Classifier Generative Adversarial Networks. - Chi Nok Enoch Kan; Najibakram Maheenaboobacker; Dong Hye Ye (ISBI, 2020)

Low-Dose CT Denoising Using Octave Convolution with High and Low Frequency Bands. - Dong Kyu Won; Sion An; Sang Hyun Park 004; Dong Hye Ye (PRIME@MICCAI, 2020)

Deep Learning Approach for Dynamic Sparse Sampling for High-Throughput Mass Spectrometry Imaging. - David S. Helminiak; Hang Hu 012; Julia Laskin; Dong Hye Ye (Computational Imaging, 2021)

Breast Cancer Histopathological Image Classification with Adversarial Image Synthesis. - Saba Heidari Gheshlaghi; Chi Nok Enoch Kan; Dong Hye Ye (EMBC, 2021)

Enhancing Multi-Channel Eeg Classification with Gramian Temporal Generative Adversarial Networks. - Chi Nok Enoch Kan; Richard J. Povinelli; Dong Hye Ye (ICASSP, 2021)

Breast cancer magnification-independent multi-class histopathology classification using dual-step model. - Nathan Lang; Devansh Saxena; Tina Yen; Julie Jorns; Bing Yu; Dong Hye Ye (Digital Pathology, 2021)

Enhancing reproductive organ segmentation in pediatric CT via adversarial learning. - Chi Nok Enoch Kan; Taly Gilat Schmidt; Dong Hye Ye (Image Processing, 2021)

Deep Learning for Breast Cancer Classification of Deep Ultraviolet Fluorescence Images toward Intra-Operative Margin Assessment. - Tyrell To; Saba Heidari Gheshlaghi; Dong Hye Ye (EMBC, 2022)

Deep Learning From Imaging Genetics for Schizophrenia Classification. - Hongkun Yu 003; Thomas Florian; Vince D. Calhoun; Dong Hye Ye (ICIP, 2022)

Multi-Domain Neumann Network with Sensitivity Maps for Parallel MRI Reconstruction. - Jun-Hyeok Lee; Junghwa Kang; Se-Hong Oh; Dong Hye Ye (Sensors, 2022)

Fast and Robust UAV to UAV Detection and Tracking From Video. - Jing Li; Dong Hye Ye; Mathias Kolsch; Juan P. Wachs; Charles A. Bouman (IEEE Trans. Emerg. Top. Comput., 2022)

Multimodal Deep Learning for Pediatric Mild Traumatic Brain Injury Detection. - Badhan Mazumder; Deepan Krishna Tripathy; Keith Owen Yeates; Miriam H. Beauchamp; William Craig; Quynh Doan; Stephen B. Freedman; Catherine Lebel; Roger Zemek; Ashley L. Ware; Dong Hye Ye (BHI, 2023)

Multi-Modal Deep Learning on Imaging Genetics for Schizophrenia Classification. - Ayush Kanyal; Srinivas Kandula; Vince D. Calhoun; Dong Hye Ye (ICASSP Workshops, 2023)

Deep Learning Approach for Dynamic Sampling for Multichannel Mass Spectrometry Imaging. - David S. Helminiak; Hang Hu 012; Julia Laskin; Dong Hye Ye (IEEE Trans. Computational Imaging, 2023)

Machine Learning Models for Prediction of Metal Ion Concentrations in Drinking Water. - Nehpal S. Shekhawat; Sangmin Oh; Cristinel Ababei; Chung Hoon Lee; Dong Hye Ye (EIT, 2024)

Scepter: Weakly Supervised Framework for Spatiotemporal Dense Prediction of 4D Dynamic Brain Networks. - Behnam Kazemivash; Pranav Suresh; Jingyu Liu 001; Dong Hye Ye; Vince D. Calhoun (EMBC, 2024)

Guided Context Gating: Learning To Leverage Salient Lesions in Retinal Fundus Images. - Teja Krishna Cherukuri; Nagur Shareef Shaik; Dong Hye Ye (ICIP, 2024)

M3T: Multi-Modal Medical Transformer To Bridge Clinical Context With Visual Insights For Retinal Image Medical Description Generation. - Nagur Shareef Shaik; Teja Krishna Cherukuri; Dong Hye Ye (ICIP, 2024)

Deep Learning for Automated Detection of Breast Cancer in Deep Ultraviolet Fluorescence Images with Diffusion Probabilistic Model. - Sepehr Salem Ghahfarokhi; Tyrell To; Julie Jorns; Tina Yen; Bing Yu; Dong Hye Ye (ISBI, 2024)

Spatial Sequence Attention Network for Schizophrenia Classification from Structural Brain MR Images. - Nagur Shareef Shaik; Teja Krishna Cherukuri; Vince D. Calhoun; Dong Hye Ye (ISBI, 2024)

Physics-Guided Multi-view Graph Neural Network for Schizophrenia Classification via Structural-Functional Coupling. - Badhan Mazumder; Ayush Kanyal; Lei Wu 013; Vince D. Calhoun; Dong Hye Ye (PRIME@MICCAI, 2024)

GCS-M3VLT: Guided Context Self-Attention based Multi-modal Medical Vision Language Transformer for Retinal Image Captioning. - Teja Krishna Cherukuri; Nagur Shareef Shaik; Jyostna Devi Bodapati; Dong Hye Ye (ICASSP, 2025)

Genetics Encoded Joint Embedding of Multimodal Connectomes with Explainable Graph Neural Network for Schizophrenia Classification. - Badhan Mazumder; Lei Wu 013; Vince D. Calhoun; Dong Hye Ye (ISBI, 2025)

Multi-Modal Imaging Genomics Transformer: Attentive Integration of Imaging with Genomic Biomarkers for Schizophrenia Classification. - Nagur Shareef Shaik; Teja Krishna Cherukuri; Vince D. Calhoun; Dong Hye Ye (ISBI, 2025)

A preliminary attempt to harmonize using physics-constrained deep neural networks for multisite and multiscanner MRI datasets (PhyCHarm). - Gawon Lee; Dong Hye Ye; Se-Hong Oh 001 (NeuroImage, 2025)

Dynamic Contextual Attention Network: Transforming Spatial Representations into Adaptive Insights for Endoscopic Polyp Diagnosis. - Teja Krishna Cherukuri; Nagur Shareef Shaik; Sribhuvan Reddy Yellu; Jun-Won Chung; Dong Hye Ye (CoRR, 2025)

Breast Cancer Classification in Deep Ultraviolet Fluorescence Images Using a Patch-Level Vision Transformer Framework. - Pouya Afshin; David S. Helminiak; Tongtong Lu; Tina Yen; Julie Jorns; Mollie Patton; Bing Yu; Dong Hye Ye (CoRR, 2025)

Unified Cross-Modal Attention-Mixer Based Structural-Functional Connectomics Fusion for Neuropsychiatric Disorder Diagnosis. - Badhan Mazumder; Lei Wu 013; Vince D. Calhoun; Dong Hye Ye (CoRR, 2025)