20 citations · 40 across the 24 of their papers we have counts for
17 papers · 1 filter
Warm-Started Reinforcement Learning for Iterative 3D/2D Liver Registration
Hanyuan Zhang, Lucas He, Zijie Cheng +5
Registration between preoperative CT and intraoperative laparoscopic video plays a crucial role in augmented reality (AR) guidance for minimally invasive surgery. Learning-based me…
Flow Matching-enabled Test-Time Refinement for Unsupervised Cardiac MR Registration
Yunguan Fu, Wenjia Bai, Wen Yan +3
Diffusion-based unsupervised image registration has been explored for cardiac cine MR, but expensive multi-step inference limits practical use. We propose FlowReg, a flow-matching…
Depth Augmented and FE Free 3D/2D Liver Registration for Laparoscopic Liver AR
Hanyuan Zhang, Lucas He, Runlong He +6
Augmented reality (AR) guidance in laparoscopic liver surgery requires accurate registration of preoperative 3D models to intraoperative 2D video, but remains challenging due to pa…
SurgAnt-ViVQA: Learning to Anticipate Surgical Events through GRU-Driven Temporal Cross-Attention
Shreyas C. Dhake, Jiayuan Huang, Runlong He +7
Anticipating forthcoming surgical events is vital for real-time assistance in endonasal transsphenoidal pituitary surgery, where visibility is limited and workflow changes rapidly.…
Subsampled Randomized Fourier GaLore for Adapting Foundation Models in Depth-Driven Liver Landmark Segmentation
Yun-Chen Lin, Jiayuan Huang, Hanyuan Zhang +3
Accurate detection and delineation of anatomical structures in medical imaging are critical for computer-assisted interventions, particularly in laparoscopic liver surgery where 2D…
C3VDReg: A Benchmark for Local-to-Local Colonoscopic Registration toward Anatomical Localization
Linzhe Jiang, Jiayuan Huang, Sophia Bano +3
Anatomy-aware colonoscopic navigation requires localizing partial endoscopic observations on a stable 3D reference to support coverage assessment, revisited-region awareness, and C…
EndoSfM3D: Learning to 3D Reconstruct Any Endoscopic Surgery Scene using Self-supervised Foundation Model
Changhao Zhang, Matthew J. Clarkson, Mobarak I. Hoque
3D reconstruction of endoscopic surgery scenes plays a vital role in enhancing scene perception, enabling AR visualization, and supporting context-aware decision-making in image-gu…
Reasoning in machine vision by learning fast and slow thinking
Shaheer U. Saeed, Yipei Wang, Veeru Kasivisvanathan +4
Reasoning is a hallmark of human intelligence, enabling adaptive decision-making in complex unfamiliar scenarios. In contrast, machine intelligence remains bound to training data,…
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…
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…
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…
HUP-3D: A 3D multi-view synthetic dataset for assisted-egocentric hand-ultrasound pose estimation
Manuel Birlo, Razvan Caramalau, Philip J. "Eddie" Edwards +3
We present HUP-3D, a 3D multi-view multi-modal synthetic dataset for hand-ultrasound (US) probe pose estimation in the context of obstetric ultrasound. Egocentric markerless 3D joi…
Competing for pixels: a self-play algorithm for weakly-supervised segmentation
Shaheer U. Saeed, Shiqi Huang, João Ramalhinho +8
Weakly-supervised segmentation (WSS) methods, reliant on image-level labels indicating object presence, lack explicit correspondence between labels and regions of interest (ROIs),…
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…
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…
Weakly supervised localisation of prostate cancer using reinforcement learning for bi-parametric MR images
Martynas Pocius, Wen Yan, Dean C. Barratt +4
In this paper we propose a reinforcement learning based weakly supervised system for localisation. We train a controller function to localise regions of interest within an image by…
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…