67 citations · 385 across the 32 of their papers we have counts for
15 papers · 1 filter
CoMLP: Cooperatively-Gated MLPs for Fine-Grained Cross-Modal Information Fusion in Medical Image Segmentation
Mingyuan Meng, Shuchang Ye, Mingjian Li +3
Multi-modal medical images and clinical reports provide complementary anatomical, functional, and semantic information for medical image segmentation. Effectively exploiting these…
Localization-Infused Vision-Language Semantic Fusion for Text-Guided Medical Image Segmentation
Songyue Han, Mingye Zou, Shuchang Ye +2
Medical image segmentation is essential for modern computer-aided medicine. Recently, text-guided segmentation has shown promise by incorporating clinician-formulated textual repor…
HEad and neCK TumOR (HECKTOR) 2025: Benchmark of Segmentation, Diagnosis, and Prognosis in Multimodal PET/CT
Numan Saeed, Salma Hassan, Shahad Hardan +27
Head and neck cancers (HNC) represent a significant global health burden, with accurate tumor delineation being essential for effective radiotherapy planning. The complexity of the…
RadGenome-Anatomy: A Large-Scale Anatomy-Labeled Chest Radiograph Dataset via Physically Grounded Volumetric Projection
Shuchang Ye, Mingyuan Meng, Hao Wang +2
Anatomical structure labels for chest radiographs are essential for medical image segmentation and a broad range of downstream diagnostic tasks. However, annotating anatomy directl…
Alleviating Textual Reliance in Medical Language-guided Segmentation via Prototype-driven Semantic Approximation
Shuchang Ye, Usman Naseem, Mingyuan Meng +1
Medical language-guided segmentation, integrating textual clinical reports as auxiliary guidance to enhance image segmentation, has demonstrated significant improvements over unimo…
MedCFVQA: A Causal Approach to Mitigate Modality Preference Bias in Medical Visual Question Answering
Shuchang Ye, Usman Naseem, Mingyuan Meng +2
Medical Visual Question Answering (MedVQA) is crucial for enhancing the efficiency of clinical diagnosis by providing accurate and timely responses to clinicians' inquiries regardi…
Language-guided Medical Image Segmentation with Target-informed Multi-level Contrastive Alignments
Mingjian Li, Mingyuan Meng, Shuchang Ye +4
Medical image segmentation is a fundamental task in numerous medical engineering applications. Recently, language-guided segmentation has shown promise in medical scenarios where t…
SGSeg: Enabling Text-free Inference in Language-guided Segmentation of Chest X-rays via Self-guidance
Shuchang Ye, Mingyuan Meng, Mingjian Li +2
Segmentation of infected areas in chest X-rays is pivotal for facilitating the accurate delineation of pulmonary structures and pathological anomalies. Recently, multi-modal langua…
Dynamic Traceback Learning for Medical Report Generation
Shuchang Ye, Mingyuan Meng, Mingjian Li +3
Automated medical report generation has demonstrated the potential to significantly reduce the workload associated with time-consuming medical reporting. Recent generative represen…
Enhancing medical vision-language contrastive learning via inter-matching relation modelling
Mingjian Li, Mingyuan Meng, Michael Fulham +3
Medical image representations can be learned through medical vision-language contrastive learning (mVLCL) where medical imaging reports are used as weak supervision through image-t…
Non-iterative Coarse-to-fine Transformer Networks for Joint Affine and Deformable Image Registration
Mingyuan Meng, Lei Bi, Michael Fulham +2
Image registration is a fundamental requirement for medical image analysis. Deep registration methods based on deep learning have been widely recognized for their capabilities to p…
Biomedical image analysis competitions: The state of current participation practice
Matthias Eisenmann, Annika Reinke, Vivienn Weru +352
The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…
Brain Tumor Sequence Registration with Non-iterative Coarse-to-fine Networks and Dual Deep Supervision
Mingyuan Meng, Lei Bi, Dagan Feng +1
In this study, we focus on brain tumor sequence registration between pre-operative and follow-up Magnetic Resonance Imaging (MRI) scans of brain glioma patients, in the context of…
Non-iterative Coarse-to-fine Registration based on Single-pass Deep Cumulative Learning
Mingyuan Meng, Lei Bi, Dagan Feng +1
Deformable image registration is a crucial step in medical image analysis for finding a non-linear spatial transformation between a pair of fixed and moving images. Deep registrati…
Enhancing Medical Image Registration via Appearance Adjustment Networks
Mingyuan Meng, Lei Bi, Michael Fulham +2
Deformable image registration is fundamental for many medical image analyses. A key obstacle for accurate image registration lies in image appearance variations such as the variati…