11 citations · 37 across the 13 of their papers we have counts for
13 papers
LUMEN: Longitudinal Multi-Modal Radiology Model for Prognosis and Diagnosis
Zhifan Jiang, Dong Yang, Vishwesh Nath +7
Large vision-language models (VLMs) have evolved from general-purpose applications to specialized use cases such as in the clinical domain, demonstrating potential for decision sup…
Text2CT: Towards 3D CT Volume Generation from Free-text Descriptions Using Diffusion Model
Pengfei Guo, Can Zhao, Dong Yang +9
Generating 3D CT volumes from descriptive free-text inputs presents a transformative opportunity in diagnostics and research. In this paper, we introduce Text2CT, a novel approach…
C-FedRAG: A Confidential Federated Retrieval-Augmented Generation System
Parker Addison, Minh-Tuan H. Nguyen, Tomislav Medan +13
Organizations seeking to utilize Large Language Models (LLMs) for knowledge querying and analysis often encounter challenges in maintaining an LLM fine-tuned on targeted, up-to-dat…
VILA-M3: Enhancing Vision-Language Models with Medical Expert Knowledge
Vishwesh Nath, Wenqi Li, Dong Yang +22
Generalist vision language models (VLMs) have made significant strides in computer vision, but they fall short in specialized fields like healthcare, where expert knowledge is esse…
MAISI: Medical AI for Synthetic Imaging
Pengfei Guo, Can Zhao, Dong Yang +8
Medical imaging analysis faces challenges such as data scarcity, high annotation costs, and privacy concerns. This paper introduces the Medical AI for Synthetic Imaging (MAISI), an…
A Short Review and Evaluation of SAM2's Performance in 3D CT Image Segmentation
Yufan He, Pengfei Guo, Yucheng Tang +7
Since the release of Segment Anything 2 (SAM2), the medical imaging community has been actively evaluating its performance for 3D medical image segmentation. However, different stu…
Supercharging Federated Learning with Flower and NVIDIA FLARE
Holger R. Roth, Daniel J. Beutel, Yan Cheng +13
Several open-source systems, such as Flower and NVIDIA FLARE, have been developed in recent years while focusing on different aspects of federated learning (FL). Flower is dedicate…
HoloHisto: End-to-end Gigapixel WSI Segmentation with 4K Resolution Sequential Tokenization
Yucheng Tang, Yufan He, Vishwesh Nath +11
In digital pathology, the traditional method for deep learning-based image segmentation typically involves a two-stage process: initially segmenting high-resolution whole slide ima…
Data Alchemy: Mitigating Cross-Site Model Variability Through Test Time Data Calibration
Abhijeet Parida, Antonia Alomar, Zhifan Jiang +7
Deploying deep learning-based imaging tools across various clinical sites poses significant challenges due to inherent domain shifts and regulatory hurdles associated with site-spe…
VISTA3D: A Unified Segmentation Foundation Model For 3D Medical Imaging
Yufan He, Pengfei Guo, Yucheng Tang +11
Foundation models for interactive segmentation in 2D natural images and videos have sparked significant interest in building 3D foundation models for medical imaging. However, the…
Empowering Federated Learning for Massive Models with NVIDIA FLARE
Holger R. Roth, Ziyue Xu, Yuan-Ting Hsieh +12
In the ever-evolving landscape of artificial intelligence (AI) and large language models (LLMs), handling and leveraging data effectively has become a critical challenge. Most stat…
FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models
Jingwei Sun, Ziyue Xu, Hongxu Yin +4
Pre-trained language models (PLM) have revolutionized the NLP landscape, achieving stellar performances across diverse tasks. These models, while benefiting from vast training data…
Federated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan
Dong Yang, Ziyue Xu, Wenqi Li +17
The recent outbreak of COVID-19 has led to urgent needs for reliable diagnosis and management of SARS-CoV-2 infection. As a complimentary tool, chest CT has been shown to be able t…