57 citations · 67 across the 9 of their papers we have counts for
9 papers
Concept-Guided Noisy Negative Suppression for Zero-Shot Classification and Grounding of Chest X-Ray Findings
Chenyu Lian, Hong-Yu Zhou, Chun-Ka Wong +1
Vision-language alignment using chest X-rays and radiology reports has emerged as an advanced paradigm for zero-shot classification and grounding of chest X-ray findings. However,…
Evidential Reasoning Advances Interpretable Real-World Disease Screening
Chenyu Lian, Hong-Yu Zhou, Jing Qin
Disease screening is critical for early detection and timely intervention in clinical practice. However, most current screening models for medical images suffer from limited interp…
BioVFM-21M: Benchmarking and Scaling Self-Supervised Vision Foundation Models for Biomedical Image Analysis
Jiarun Liu, Hong-Yu Zhou, Weijian Huang +5
Scaling up model and data size have demonstrated impressive performance improvement over a wide range of tasks. Despite extensive studies on scaling behaviors for general-purpose t…
Swin-UMamba: Mamba-based UNet with ImageNet-based pretraining
Jiarun Liu, Hao Yang, Hong-Yu Zhou +8
Accurate medical image segmentation demands the integration of multi-scale information, spanning from local features to global dependencies. However, it is challenging for existing…
Enhancing Representation in Medical Vision-Language Foundation Models via Multi-Scale Information Extraction Techniques
Weijian Huang, Cheng Li, Hong-Yu Zhou +6
The development of medical vision-language foundation models has attracted significant attention in the field of medicine and healthcare due to their promising prospect in various…
MLIP: Medical Language-Image Pre-training with Masked Local Representation Learning
Jiarun Liu, Hong-Yu Zhou, Cheng Li +4
Existing contrastive language-image pre-training aims to learn a joint representation by matching abundant image-text pairs. However, the number of image-text pairs in medical data…
A multi-modal vision-language model for generalizable annotation-free pathology localization
Hao Yang, Hong-Yu Zhou, Jiarun Liu +12
Existing deep learning models for defining pathology from clinical imaging data rely on expert annotations and lack generalization capabilities in open clinical environments. Here,…
Multimodal self-supervised learning for lesion localization
Hao Yang, Hong-Yu Zhou, Cheng Li +7
Multimodal deep learning utilizing imaging and diagnostic reports has made impressive progress in the field of medical imaging diagnostics, demonstrating a particularly strong capa…
Enhancing Representation in Radiography-Reports Foundation Model: A Granular Alignment Algorithm Using Masked Contrastive Learning
Weijian Huang, Cheng Li, Hong-Yu Zhou +6
Recently, multi-modal vision-language foundation models have gained significant attention in the medical field. While these models offer great opportunities, they still face crucia…