most citedAn objective comparison of methods for augmented reality in laparoscopic liver resection by preoperative-to-intraoperative image fusion

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

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…

eess.IV2025

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…

cs.CV2025

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…

cs.CV2024

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'…

cs.CV2024★ 1 cited

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…