67 citations · 140 across the 48 of their papers we have counts for
35 papers · 1 filter
SurgiATM: A Physics-Guided Plug-and-Play Model for Deep Learning-Based Smoke Removal in Laparoscopic Surgery
Mingyu Sheng, Jianan Fan, Dongnan Liu +3
During laparoscopic surgery, smoke generated by tissue cauterization can significantly degrade the visual quality of endoscopic frames, increasing the risk of surgical errors and h…
Towards Conditional Feature Alignment for Cross-Domain Counting
Zhuonan Liang, Dongnan Liu, Jianan Fan +6
Object counting models often degrade under cross-domain deployment because density composition varies across domains and is itself task-relevant. Standard feature alignment methods…
MultiCo3D: Multi-Label Voxel Contrast for One-Shot Incremental Segmentation of 3D Neuroimages
Hao Xu, Tengfei Xue, Dongnan Liu +6
3D neuroimages provide a comprehensive view of brain structure and function, aiding in precise localization and functional connectivity analysis. Segmentation of white matter (WM)…
MIRROR: Multi-Modal Pathological Self-Supervised Representation Learning via Modality Alignment and Retention
Tianyi Wang, Jianan Fan, Dingxin Zhang +4
Histopathology and transcriptomics are fundamental modalities in oncology, encapsulating the morphological and molecular aspects of the disease. Multi-modal self-supervised learnin…
Medical Image Registration Meets Vision Foundation Model: Prototype Learning and Contour Awareness
Hao Xu, Tengfei Xue, Jianan Fan +7
Medical image registration is a fundamental task in medical image analysis, aiming to establish spatial correspondences between paired images. However, existing unsupervised deform…
RealSyn: An Effective and Scalable Multimodal Interleaved Document Transformation Paradigm
Tiancheng Gu, Kaicheng Yang, Chaoyi Zhang +6
After pre-training on extensive image-text pairs, Contrastive Language-Image Pre-training (CLIP) demonstrates promising performance on a wide variety of benchmarks. However, a subs…
Cross-View Consistency Regularisation for Knowledge Distillation
Weijia Zhang, Dongnan Liu, Weidong Cai +1
Knowledge distillation (KD) is an established paradigm for transferring privileged knowledge from a cumbersome model to a lightweight and efficient one. In recent years, logit-base…
ORID: Organ-Regional Information Driven Framework for Radiology Report Generation
Tiancheng Gu, Kaicheng Yang, Xiang An +3
The objective of Radiology Report Generation (RRG) is to automatically generate coherent textual analyses of diseases based on radiological images, thereby alleviating the workload…
AMNCutter: Affinity-Attention-Guided Multi-View Normalized Cutter for Unsupervised Surgical Instrument Segmentation
Mingyu Sheng, Jianan Fan, Dongnan Liu +2
Surgical instrument segmentation (SIS) is pivotal for robotic-assisted minimally invasive surgery, assisting surgeons by identifying surgical instruments in endoscopic video frames…
TractShapeNet: Efficient Multi-Shape Learning with 3D Tractography Point Clouds
Yui Lo, Yuqian Chen, Dongnan Liu +9
Brain imaging studies have demonstrated that diffusion MRI tractography geometric shape descriptors can inform the study of the brain's white matter pathways and their relationship…
Enhancing Advanced Visual Reasoning Ability of Large Language Models
Zhiyuan Li, Dongnan Liu, Chaoyi Zhang +3
Recent advancements in Vision-Language (VL) research have sparked new benchmarks for complex visual reasoning, challenging models' advanced reasoning ability. Traditional Vision-La…
Revisiting Surgical Instrument Segmentation Without Human Intervention: A Graph Partitioning View
Mingyu Sheng, Jianan Fan, Dongnan Liu +2
Surgical instrument segmentation (SIS) on endoscopic images stands as a long-standing and essential task in the context of computer-assisted interventions for boosting minimally in…
Multimodal Causal Reasoning Benchmark: Challenging Vision Large Language Models to Discern Causal Links Across Modalities
Zhiyuan Li, Heng Wang, Dongnan Liu +4
Multimodal Large Language Models (MLLMs) have showcased exceptional Chain-of-Thought (CoT) reasoning ability in complex textual inference tasks including causal reasoning. However,…
White Matter Geometry-Guided Score-Based Diffusion Model for Tissue Microstructure Imputation in Tractography Imaging
Yui Lo, Yuqian Chen, Fan Zhang +6
Parcellation of white matter tractography provides anatomical features for disease prediction, anatomical tract segmentation, surgical brain mapping, and non-imaging phenotype clas…
Enhancing Robustness to Noise Corruption for Point Cloud Recognition via Spatial Sorting and Set-Mixing Aggregation Module
Dingxin Zhang, Jianhui Yu, Tengfei Xue +3
Current models for point cloud recognition demonstrate promising performance on synthetic datasets. However, real-world point cloud data inevitably contains noise, impacting model…
RWKV-CLIP: A Robust Vision-Language Representation Learner
Tiancheng Gu, Kaicheng Yang, Xiang An +4
Contrastive Language-Image Pre-training (CLIP) has significantly improved performance in various vision-language tasks by expanding the dataset with image-text pairs obtained from…
Dance Any Beat: Blending Beats with Visuals in Dance Video Generation
Xuanchen Wang, Heng Wang, Dongnan Liu +1
Generating dance from music is crucial for advancing automated choreography. Current methods typically produce skeleton keypoint sequences instead of dance videos and lack the capa…
LaPA: Latent Prompt Assist Model For Medical Visual Question Answering
Tiancheng Gu, Kaicheng Yang, Dongnan Liu +1
Medical visual question answering (Med-VQA) aims to automate the prediction of correct answers for medical images and questions, thereby assisting physicians in reducing repetitive…
Cross-domain Fiber Cluster Shape Analysis for Language Performance Cognitive Score Prediction
Yui Lo, Yuqian Chen, Dongnan Liu +8
Shape plays an important role in computer graphics, offering informative features to convey an object's morphology and functionality. Shape analysis in brain imaging can help inter…
Multi-source-free Domain Adaptation via Uncertainty-aware Adaptive Distillation
Yaxuan Song, Jianan Fan, Dongnan Liu +1
Source-free domain adaptation (SFDA) alleviates the domain discrepancy among data obtained from domains without accessing the data for the awareness of data privacy. However, exist…
Learning to Generalize over Subpartitions for Heterogeneity-aware Domain Adaptive Nuclei Segmentation
Jianan Fan, Dongnan Liu, Hang Chang +1
Annotation scarcity and cross-modality/stain data distribution shifts are two major obstacles hindering the application of deep learning models for nuclei analysis, which holds a b…
Complex Organ Mask Guided Radiology Report Generation
Tiancheng Gu, Dongnan Liu, Zhiyuan Li +1
The goal of automatic report generation is to generate a clinically accurate and coherent phrase from a single given X-ray image, which could alleviate the workload of traditional…
ODM3D: Alleviating Foreground Sparsity for Semi-Supervised Monocular 3D Object Detection
Weijia Zhang, Dongnan Liu, Chao Ma +1
Monocular 3D object detection (M3OD) is a significant yet inherently challenging task in autonomous driving due to absence of explicit depth cues in a single RGB image. In this pap…
Taxonomy Adaptive Cross-Domain Adaptation in Medical Imaging via Optimization Trajectory Distillation
Jianan Fan, Dongnan Liu, Hang Chang +3
The success of automated medical image analysis depends on large-scale and expert-annotated training sets. Unsupervised domain adaptation (UDA) has been raised as a promising appro…