51 citations · 58 across the 12 of their papers we have counts for
6 papers · 1 filter
MedVL-SAM2: A unified 3D medical vision-language model for multimodal reasoning and prompt-driven segmentation
Yang Xing, Jiong Wu, Savas Ozdemir +4
Recent progress in medical vision-language models (VLMs) has achieved strong performance on image-level text-centric tasks such as report generation and visual question answering (…
SAM2-SGP: Enhancing SAM2 for Medical Image Segmentation via Support-Set Guided Prompting
Yang Xing, Jiong Wu, Yuheng Bu +1
Although new vision foundation models such as Segment Anything Model 2 (SAM2) have significantly enhanced zero-shot image segmentation capabilities, reliance on human-provided prom…
CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation
Jiong Wu, Yang Xing, Boxiao Yu +2
Most publicly available medical segmentation datasets are only partially labeled, with annotations provided for a subset of anatomical structures. When multiple datasets are combin…
LDM-Morph: Latent diffusion model guided deformable image registration
Jiong Wu, Kuang Gong
Deformable image registration plays an essential role in various medical image tasks. Existing deep learning-based deformable registration frameworks primarily utilize convolutiona…
Fast Diffeomorphic Image Registration using Patch based Fully Convolutional Networks
Jiong Wu, Shuang Zhou, Li Lin +2
Diffeomorphic image registration is a fundamental step in medical image analysis, owing to its capability to ensure the invertibility of transformations and preservation of topolog…
Brain segmentation based on multi-atlas guided 3D fully convolutional network ensembles
Jiong Wu, Xiaoying Tang
In this study, we proposed and validated a multi-atlas guided 3D fully convolutional network (FCN) ensemble model (M-FCN) for segmenting brain regions of interest (ROIs) from struc…