12 citations · 14 across the 12 of their papers we have counts for
13 papers
TCMScience: An Autonomous Scientist for Traditional Chinese Medicine
Yanlan Kang, Ruiqi Liu, Xinpei Gu +4
Traditional Chinese medicine (TCM) research connects classical texts, medicinal entities, molecular assays, computational predictions, and clinical studies. An autonomous research…
Vis2Reg: Visibility-Aware Landmark-Free Geometric 3D--2D Registration for Liver Laparoscopy
Jiaming Feng, Xukun Zhang, Shahid Farid +1
Accurate 3D--2D liver registration, which aligns preoperative 3D models to partial, view-dependent intraoperative surface observations, is critical for AR-guided laparoscopic surge…
Adaptive Reinforcement for Open-ended Medical Reasoning via Semantic-Guided Reward Collapse Mitigation
Yizhou Liu, Dingkang Yang, Zizhi Chen +5
Reinforcement learning (RL) with rule-based reward functions has recently shown great promise in enhancing the reasoning depth and generalization ability of vision-language models…
VLM-based Prompts as the Optimal Assistant for Unpaired Histopathology Virtual Staining
Zizhi Chen, Xinyu Zhang, Minghao Han +6
In histopathology, tissue sections are typically stained using common H&E staining or special stains (MAS, PAS, PASM, etc.) to clearly visualize specific tissue structures. The rap…
VGAT: A Cancer Survival Analysis Framework Transitioning from Generative Visual Question Answering to Genomic Reconstruction
Zizhi Chen, Minghao Han, Xukun Zhang +4
Multimodal learning combining pathology images and genomic sequences enhances cancer survival analysis but faces clinical implementation barriers due to limited access to genomic s…
Towards Unified Molecule-Enhanced Pathology Image Representation Learning via Integrating Spatial Transcriptomics
Minghao Han, Dingkang Yang, Jiabei Cheng +4
Recent advancements in multimodal pre-training models have significantly advanced computational pathology. However, current approaches predominantly rely on visual-language models,…
MaskBEV: Towards A Unified Framework for BEV Detection and Map Segmentation
Xiao Zhao, Xukun Zhang, Dingkang Yang +4
Accurate and robust multimodal multi-task perception is crucial for modern autonomous driving systems. However, current multimodal perception research follows independent paradigms…
HybridOcc: NeRF Enhanced Transformer-based Multi-Camera 3D Occupancy Prediction
Xiao Zhao, Bo Chen, Mingyang Sun +7
Vision-based 3D semantic scene completion (SSC) describes autonomous driving scenes through 3D volume representations. However, the occlusion of invisible voxels by scene surfaces…
MSCPT: Few-shot Whole Slide Image Classification with Multi-scale and Context-focused Prompt Tuning
Minghao Han, Linhao Qu, Dingkang Yang +3
Multiple instance learning (MIL) has become a standard paradigm for the weakly supervised classification of whole slide images (WSIs). However, this paradigm relies on using a larg…
Multi-Scale Heterogeneity-Aware Hypergraph Representation for Histopathology Whole Slide Images
Minghao Han, Xukun Zhang, Dingkang Yang +4
Survival prediction is a complex ordinal regression task that aims to predict the survival coefficient ranking among a cohort of patients, typically achieved by analyzing patients'…
An objective comparison of methods for augmented reality in laparoscopic liver resection by preoperative-to-intraoperative image fusion
Sharib Ali, Yamid Espinel, Yueming Jin +17
Augmented reality for laparoscopic liver resection is a visualisation mode that allows a surgeon to localise tumours and vessels embedded within the liver by projecting them on top…
Tissue Segmentation of Thick-Slice Fetal Brain MR Scans with Guidance from High-Quality Isotropic Volumes
Shijie Huang, Xukun Zhang, Zhiming Cui +3
Accurate tissue segmentation of thick-slice fetal brain magnetic resonance (MR) scans is crucial for both reconstruction of isotropic brain MR volumes and the quantification of fet…
Pyramid Focusing Network for mutation prediction and classification in CT images
Xukun Zhang, Wenxin Hu, Wen Wu
Predicting the mutation status of genes in tumors is of great clinical significance. Recent studies have suggested that certain mutations may be noninvasively predicted by studying…