2 citations · 3 across the 19 of their papers we have counts for
20 papers
MedPMC: A Systematic Framework for Scaling High-Fidelity Medical Multimodal Data for Foundation Models
Hyunjae Kim, Dain Kim, Pan Xiao +25
Medicine is inherently multimodal, requiring clinicians to synthesize information across diverse data streams. Yet the development of multimodal foundation models is constrained by…
MammoFlow: Multiview Mammogram Synthesis with Anatomically Consistent Flow Matching
Yuexi Du, Leya Barrientos, Laura Sheiman +3
Multiview mammography relies on paired craniocaudal (CC) and mediolateral oblique (MLO) views to provide complementary projections of a 3D breast volume, enabling precise anomaly l…
Benchmarking Ultrasound Foundation Models for Fetal Plane Classification
Leya Barrientos, Yuexi Du, Nicha C. Dvornek
Ultrasound is widely used in obstetric care due to its safety, accessibility, and real-time imaging. However, interpretation remains operator-dependent and susceptible to noise and…
BioFact-MoE: Biologically Factorized Mixture of Experts for Vision-Language Prognostic Modeling in Hepatocellular Carcinoma
Junlin Yang, Tian Yu, Nicha C. Dvornek +6
Hepatocellular carcinoma (HCC) is biologically heterogeneous, shaped by the interplay between hepatic functional reserve and tumor-related oncologic factors; thus, similar survival…
CARE: Towards Clinical Accountability in Multi-Modal Medical Reasoning with an Evidence-Grounded Agentic Framework
Yuexi Du, Jinglu Wang, Shujie Liu +2
Large visual language models (VLMs) have shown strong multi-modal medical reasoning ability, but most operate as end-to-end black boxes, diverging from clinicians' evidence-based,…
DECADE: A Temporally-Consistent Unsupervised Diffusion Model for Enhanced Rb-82 Dynamic Cardiac PET Image Denoising
Yinchi Zhou, Liang Guo, Huidong Xie +14
Rb-82 dynamic cardiac PET imaging is widely used for the clinical diagnosis of coronary artery disease (CAD), but its short half-life results in high noise levels that degrade dyna…
Equi-ViT: Rotational Equivariant Vision Transformer for Robust Histopathology Analysis
Fuyao Chen, Yuexi Du, Elèonore V. Lieffrig +2
Vision Transformers (ViTs) have gained rapid adoption in computational pathology for their ability to model long-range dependencies through self-attention, addressing the limitatio…
Acquisition Time-Informed Breast Tumor Segmentation from Dynamic Contrast-Enhanced MRI
Rui Wang, Yuexi Du, John Lewin +2
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays an important role in breast cancer screening, tumor assessment, and treatment planning and monitoring. The dyna…
GLAM: Geometry-Guided Local Alignment for Multi-View VLP in Mammography
Yuexi Du, Lihui Chen, Nicha C. Dvornek
Mammography screening is an essential tool for early detection of breast cancer. The speed and accuracy of mammography interpretation have the potential to be improved with deep le…
CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray
Mingquan Lin, Gregory Holste, Song Wang +30
The CXR-LT series is a community-driven initiative designed to enhance lung disease classification using chest X-rays (CXR). It tackles challenges in open long-tailed lung disease…
Equivariant Imaging Biomarkers for Robust Unsupervised Segmentation of Histopathology
Fuyao Chen, Yuexi Du, Tal Zeevi +2
Histopathology evaluation of tissue specimens through microscopic examination is essential for accurate disease diagnosis and prognosis. However, traditional manual analysis by spe…
GMR-Conv: An Efficient Rotation and Reflection Equivariant Convolution Kernel Using Gaussian Mixture Rings
Yuexi Du, Jiazhen Zhang, Nicha C. Dvornek +1
Symmetry, where certain features remain invariant under geometric transformations, can often serve as a powerful prior in designing convolutional neural networks (CNNs). While conv…
Improved Vessel Segmentation with Symmetric Rotation-Equivariant U-Net
Jiazhen Zhang, Yuexi Du, Nicha C. Dvornek +1
Automated segmentation plays a pivotal role in medical image analysis and computer-assisted interventions. Despite the promising performance of existing methods based on convolutio…
SRE-Conv: Symmetric Rotation Equivariant Convolution for Biomedical Image Classification
Yuexi Du, Jiazhen Zhang, Tal Zeevi +2
Convolutional neural networks (CNNs) are essential tools for computer vision tasks, but they lack traditionally desired properties of extracted features that could further improve…
Self-Supervised Pre-training Tasks for an fMRI Time-series Transformer in Autism Detection
Yinchi Zhou, Peiyu Duan, Yuexi Du +1
Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that encompasses a wide variety of symptoms and degrees of impairment, which makes the diagnosis and treatment chal…
Multi-View and Multi-Scale Alignment for Contrastive Language-Image Pre-training in Mammography
Yuexi Du, John Onofrey, Nicha C. Dvornek
Contrastive Language-Image Pre-training (CLIP) demonstrates strong potential in medical image analysis but requires substantial data and computational resources. Due to these restr…
CLEFT: Language-Image Contrastive Learning with Efficient Large Language Model and Prompt Fine-Tuning
Yuexi Du, Brian Chang, Nicha C. Dvornek
Recent advancements in Contrastive Language-Image Pre-training (CLIP) have demonstrated notable success in self-supervised representation learning across various tasks. However, th…
Spectral Brain Graph Neural Network for Prediction of Anxiety in Children with Autism Spectrum Disorder
Peiyu Duan, Nicha C. Dvornek, Jiyao Wang +4
Children with Autism Spectrum Disorder (ASD) frequently exhibit comorbid anxiety, which contributes to impairment and requires treatment. Therefore, it is critical to investigate c…
SIFT-DBT: Self-supervised Initialization and Fine-Tuning for Imbalanced Digital Breast Tomosynthesis Image Classification
Yuexi Du, Regina J. Hooley, John Lewin +1
Digital Breast Tomosynthesis (DBT) is a widely used medical imaging modality for breast cancer screening and diagnosis, offering higher spatial resolution and greater detail throug…
Conditional Generation of Audio from Video via Foley Analogies
Yuexi Du, Ziyang Chen, Justin Salamon +2
The sound effects that designers add to videos are designed to convey a particular artistic effect and, thus, may be quite different from a scene's true sound. Inspired by the chal…