223 citations · 418 across the 23 of their papers we have counts for
24 papers
Addressing Benchmarking Gaps in Large Language Models for Health and Medicine with Dynamic Red-Teaming
Jiazhen Pan, Bailiang Jian, Paul Hager +19
Large language models (LLMs) are increasingly used to answer health-related questions and support healthcare workflows, yet evidence for their safety still relies heavily on static…
AuralSAM2: Enabling SAM2 Hear Through Pyramid Audio-Visual Feature Prompting
Yuyuan Liu, Yuanhong Chen, Chong Wang +6
Segment Anything Model 2 (SAM2) exhibits strong generalisation for promptable segmentation in video clips; however, its integration with the audio modality remains underexplored. E…
PALM: Open Fundus Photograph Dataset with Pathologic Myopia Recognition and Anatomical Structure Annotation
Huihui Fang, Fei Li, Junde Wu +6
Pathologic myopia (PM) is a common blinding retinal degeneration suffered by highly myopic population. Early screening of this condition can reduce the damage caused by the associa…
Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation
Junde Wu, Wei Ji, Yuanpei Liu +4
The Segment Anything Model (SAM) has recently gained popularity in the field of image segmentation due to its impressive capabilities in various segmentation tasks and its prompt-b…
MedSegDiff-V2: Diffusion based Medical Image Segmentation with Transformer
Junde Wu, Wei Ji, Huazhu Fu +3
The Diffusion Probabilistic Model (DPM) has recently gained popularity in the field of computer vision, thanks to its image generation applications, such as Imagen, Latent Diffusio…
Multi-rater Prism: Learning self-calibrated medical image segmentation from multiple raters
Junde Wu, Huihui Fang, Yehui Yang +5
In medical image segmentation, it is often necessary to collect opinions from multiple experts to make the final decision. This clinical routine helps to mitigate individual bias.…
ExpNet: A unified network for Expert-Level Classification
Junde Wu, Huihui Fang, Yehui Yang +4
Different from the general visual classification, some classification tasks are more challenging as they need the professional categories of the images. In the paper, we call them…
MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic Model
Junde Wu, Rao Fu, Huihui Fang +5
Diffusion probabilistic model (DPM) recently becomes one of the hottest topic in computer vision. Its image generation application such as Imagen, Latent Diffusion Models and Stabl…
Learning to screen Glaucoma like the ophthalmologists
Junde Wu, Huihui Fang, Fei Li +2
GAMMA Challenge is organized to encourage the AI models to screen the glaucoma from a combination of 2D fundus image and 3D optical coherence tomography volume, like the ophthalmol…
An Efficient Person Clustering Algorithm for Open Checkout-free Groceries
Junde Wu, Yu Zhang, Rao Fu +2
Open checkout-free grocery is the grocery store where the customers never have to wait in line to check out. Developing a system like this is not trivial since it faces challenges…
Calibrate the inter-observer segmentation uncertainty via diagnosis-first principle
Junde Wu, Huihui Fang, Hoayi Xiong +5
On the medical images, many of the tissues/lesions may be ambiguous. That is why the medical segmentation is typically annotated by a group of clinical experts to mitigate the pers…
Dataset and Evaluation algorithm design for GOALS Challenge
Huihui Fang, Fei Li, Huazhu Fu +3
Glaucoma causes irreversible vision loss due to damage to the optic nerve, and there is no cure for glaucoma.OCT imaging modality is an essential technique for assessing glaucomato…
SeATrans: Learning Segmentation-Assisted diagnosis model via Transformer
Junde Wu, Huihui Fang, Fangxin Shang +5
Clinically, the accurate annotation of lesions/tissues can significantly facilitate the disease diagnosis. For example, the segmentation of optic disc/cup (OD/OC) on fundus image w…
Learning self-calibrated optic disc and cup segmentation from multi-rater annotations
Junde Wu, Huihui Fang, Fangxin Shang +5
The segmentation of optic disc(OD) and optic cup(OC) from fundus images is an important fundamental task for glaucoma diagnosis. In the clinical practice, it is often necessary to…
One Hyper-Initializer for All Network Architectures in Medical Image Analysis
Fangxin Shang, Yehui Yang, Dalu Yang +3
Pre-training is essential to deep learning model performance, especially in medical image analysis tasks where limited training data are available. However, existing pre-training m…
Contrastive Centroid Supervision Alleviates Domain Shift in Medical Image Classification
Wenshuo Zhou, Dalu Yang, Binghong Wu +6
Deep learning based medical imaging classification models usually suffer from the domain shift problem, where the classification performance drops when training data and real-world…
REFUGE2 Challenge: A Treasure Trove for Multi-Dimension Analysis and Evaluation in Glaucoma Screening
Huihui Fang, Fei Li, Junde Wu +25
With the rapid development of artificial intelligence (AI) in medical image processing, deep learning in color fundus photography (CFP) analysis is also evolving. Although there ar…
GAMMA Challenge:Glaucoma grAding from Multi-Modality imAges
Junde Wu, Huihui Fang, Fei Li +26
Color fundus photography and Optical Coherence Tomography (OCT) are the two most cost-effective tools for glaucoma screening. Both two modalities of images have prominent biomarker…
Opinions Vary? Diagnosis First!
Junde Wu, Huihui Fang, Dalu Yang +5
With the advancement of deep learning techniques, an increasing number of methods have been proposed for optic disc and cup (OD/OC) segmentation from the fundus images. Clinically,…
Progressive Hard-case Mining across Pyramid Levels for Object Detection
Binghong Wu, Yehui Yang, Dalu Yang +5
In object detection, multi-level prediction (e.g., FPN) and reweighting skills (e.g., focal loss) have drastically improved one-stage detector performance. However, the synergy bet…
TR-GAN: Topology Ranking GAN with Triplet Loss for Retinal Artery/Vein Classification
Wenting Chen, Shuang Yu, Junde Wu +5
Retinal artery/vein (A/V) classification lays the foundation for the quantitative analysis of retinal vessels, which is associated with potential risks of various cardiovascular an…
Leveraging Undiagnosed Data for Glaucoma Classification with Teacher-Student Learning
Junde Wu, Shuang Yu, Wenting Chen +5
Recently, deep learning has been adopted to the glaucoma classification task with performance comparable to that of human experts. However, a well trained deep learning model deman…
Universal, transferable and targeted adversarial attacks
Junde Wu, Rao Fu
Deep Neural Networks have been found vulnerable re-cently. A kind of well-designed inputs, which called adver-sarial examples, can lead the networks to make incorrectpredictions. D…
Integrating neural networks into the blind deblurring framework to compete with the end-to-end learning-based methods
Junde Wu, Xiaoguang Di, Jiehao Huang +1
Recently, end-to-end learning-based methods based on deep neural network (DNN) have been proven effective for blind deblurring. Without human-made assumptions and numerical algorit…