1 citations · 3 across the 7 of their papers we have counts for
8 papers
Surgical AI Copilot: Energy-Based Fourier Gradient Low-Rank Adaptation for Surgical LLM Agent Reasoning and Planning
Jiayuan Huang, Runlong He, Danyal Zaman Khan +6
Image-guided surgery demands adaptive, real-time decision support, yet static AI models struggle with structured task planning and providing interactive guidance. Large language mo…
Endo-FASt3r: Endoscopic Foundation model Adaptation for Structure from motion
Mona Sheikh Zeinoddin, Mobarak I. Hoque, Zafer Tandogdu +4
Accurate depth and camera pose estimation is essential for achieving high-quality 3D visualisations in robotic-assisted surgery. Despite recent advancements in foundation model ada…
PitVQA++: Vector Matrix-Low-Rank Adaptation for Open-Ended Visual Question Answering in Pituitary Surgery
Runlong He, Danyal Z. Khan, Evangelos B. Mazomenos +4
Vision-Language Models (VLMs) in visual question answering (VQA) offer a unique opportunity to enhance intra-operative decision-making, promote intuitive interactions, and signific…
SurgicalGS: Dynamic 3D Gaussian Splatting for Accurate Robotic-Assisted Surgical Scene Reconstruction
Jialei Chen, Xin Zhang, Mobarakol Islam +4
Accurate 3D reconstruction of dynamic surgical scenes from endoscopic video is essential for robotic-assisted surgery. While recent 3D Gaussian Splatting methods have shown promise…
DARES: Depth Anything in Robotic Endoscopic Surgery with Self-supervised Vector-LoRA of the Foundation Model
Mona Sheikh Zeinoddin, Chiara Lena, Jiongqi Qu +11
Robotic-assisted surgery (RAS) relies on accurate depth estimation for 3D reconstruction and visualization. While foundation models like Depth Anything Models (DAM) show promise, d…
PitVQA: Image-grounded Text Embedding LLM for Visual Question Answering in Pituitary Surgery
Runlong He, Mengya Xu, Adrito Das +6
Visual Question Answering (VQA) within the surgical domain, utilizing Large Language Models (LLMs), offers a distinct opportunity to improve intra-operative decision-making and fac…
Illumination Histogram Consistency Metric for Quantitative Assessment of Video Sequences
Long Chen, Mobarakol Islam, Matt Clarkson +1
The advances in deep generative models have greatly accelerate the process of video procession such as video enhancement and synthesis. Learning spatio-temporal video models requir…
Surgical-DeSAM: Decoupling SAM for Instrument Segmentation in Robotic Surgery
Yuyang Sheng, Sophia Bano, Matthew J. Clarkson +1
Purpose: The recent Segment Anything Model (SAM) has demonstrated impressive performance with point, text or bounding box prompts, in various applications. However, in safety-criti…