69 citations · 125 across the 20 of their papers we have counts for
22 papers
Computer vision enabled oxygen sensing
Nikolaos Salaris, Evangelos Mazomenos, Adrien Desjardins +1
Luminescence-based chemical sensors are almost universally read as point detectors with the signal inverted through a single calibration model. Here we reframe optical oxygen sensi…
StereoMamba: Real-time and Robust Intraoperative Stereo Disparity Estimation via Long-range Spatial Dependencies
Xu Wang, Jialang Xu, Shuai Zhang +3
Stereo disparity estimation is crucial for obtaining depth information in robot-assisted minimally invasive surgery (RAMIS). While current deep learning methods have made significa…
Point Tracking in Surgery--The 2024 Surgical Tattoos in Infrared (STIR) Challenge
Adam Schmidt, Mert Asim Karaoglu, Soham Sinha +37
Understanding tissue motion in surgery is crucial to enable applications in downstream tasks such as segmentation, 3D reconstruction, virtual tissue landmarking, autonomous probe-b…
KEVS: Enhancing Segmentation of Visceral Adipose Tissue in Pre-Cystectomy CT with Gaussian Kernel Density Estimation
Thomas Boucher, Nicholas Tetlow, Annie Fung +5
Purpose: The distribution of visceral adipose tissue (VAT) in cystectomy patients is indicative of the incidence of post-operative complications. Existing VAT segmentation methods…
EndoLRMGS: Complete Endoscopic Scene Reconstruction combining Large Reconstruction Modelling and Gaussian Splatting
Xu Wang, Shuai Zhang, Baoru Huang +2
Complete reconstruction of surgical scenes is crucial for robot-assisted surgery (RAS). Deep depth estimation is promising but existing works struggle with depth discontinuities, r…
3D Acetabular Surface Reconstruction from 2D Pre-operative X-ray Images using SRVF Elastic Registration and Deformation Graph
Shuai Zhang, Jinliang Wang, Sujith Konandetails +3
Accurate and reliable selection of the appropriate acetabular cup size is crucial for restoring joint biomechanics in total hip arthroplasty (THA). This paper proposes a novel fram…
SurgRAW: Multi-Agent Workflow with Chain of Thought Reasoning for Robotic Surgical Video Analysis
Chang Han Low, Ziyue Wang, Tianyi Zhang +4
Robotic-assisted surgery (RAS) is central to modern surgery, driving the need for intelligent systems with accurate scene understanding. Most existing surgical AI methods rely on i…
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…
From to Parameters: Quantum Self-Attention in Vision Transformers for Biomedical Image Classification
Thomas Boucher, John Whittle, Evangelos B. Mazomenos
We demonstrate that quantum vision transformers (QViTs), vision transformers (ViTs) with self-attention (SA) mechanisms replaced by quantum self-attention (QSA) mechanisms, can mat…
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…
Personalizing Federated Instrument Segmentation with Visual Trait Priors in Robotic Surgery
Jialang Xu, Jiacheng Wang, Lequan Yu +3
Personalized federated learning (PFL) for surgical instrument segmentation (SIS) is a promising approach. It enables multiple clinical sites to collaboratively train a series of mo…
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…
Think Step by Step: Chain-of-Gesture Prompting for Error Detection in Robotic Surgical Videos
Zhimin Shao, Jialang Xu, Danail Stoyanov +2
Despite significant advancements in robotic systems and surgical data science, ensuring safe and optimal execution in robot-assisted minimally invasive surgery (RMIS) remains a com…
SEDMamba: Enhancing Selective State Space Modelling with Bottleneck Mechanism and Fine-to-Coarse Temporal Fusion for Efficient Error Detection in Robot-Assisted Surgery
Jialang Xu, Nazir Sirajudeen, Matthew Boal +3
Automated detection of surgical errors can improve robotic-assisted surgery. Despite promising progress, existing methods still face challenges in capturing rich temporal context t…
Shifted-Windows Transformers for the Detection of Cerebral Aneurysms in Microsurgery
Jinfan Zhou, William Muirhead, Simon C. Williams +3
Purpose: Microsurgical Aneurysm Clipping Surgery (MACS) carries a high risk for intraoperative aneurysm rupture. Automated recognition of instances when the aneurysm is exposed in…
Objective Surgical Skills Assessment and Tool Localization: Results from the MICCAI 2021 SimSurgSkill Challenge
Aneeq Zia, Kiran Bhattacharyya, Xi Liu +12
Timely and effective feedback within surgical training plays a critical role in developing the skills required to perform safe and efficient surgery. Feedback from expert surgeons,…
Towards a Computed-Aided Diagnosis System in Colonoscopy: Automatic Polyp Segmentation Using Convolution Neural Networks
Patrick Brandao, Odysseas Zisimopoulos, Evangelos Mazomenos +9
Early diagnosis is essential for the successful treatment of bowel cancers including colorectal cancer (CRC) and capsule endoscopic imaging with robotic actuation can be a valuable…
Automated Performance Assessment in Transoesophageal Echocardiography with Convolutional Neural Networks
Evangelos B. Mazomenos, Kamakshi Bansal, Bruce Martin +3
Transoesophageal echocardiography (TEE) is a valuable diagnostic and monitoring imaging modality. Proper image acquisition is essential for diagnosis, yet current assessment techni…
Widening siamese architectures for stereo matching
Patrick Brandao, Evangelos Mazomenos, Danail Stoyanov
Computational stereo is one of the classical problems in computer vision. Numerous algorithms and solutions have been reported in recent years focusing on developing methods for co…
A Statistical Index for Early Diagnosis of Ventricular Arrhythmia from the Trend Analysis of ECG Phase-portraits
Grazia Cappiello, Saptarshi Das, Evangelos B. Mazomenos +4
In this paper, we propose a novel statistical index for the early diagnosis of ventricular arrhythmia (VA) using the time delay phase-space reconstruction (PSR) technique, from the…
A novel approach for the diagnosis of ventricular tachycardia based on phase space reconstruction of ECG
George Koulaouzidis, Saptarshi Das, Grazia Cappiello +3
Ventricular arrhythmias comprise a group of disorders which manifest clinically in a variety of ways from ventricular premature beats (VPB) and no sustained ventricular tachycardia…