Surgery

Interpretable Transformer-Based Phase Recognition for Transabdominal Preperitoneal Laparoscopic Inguinal Hernia Repair

Background: Surgical phase recognition is a critical prerequisite for context-aware operating rooms and automated skill assessment. While artificial intelligence (AI) benchmarking has progressed for simpler procedures, applying surgical phase recognition to complex, anatomically demanding operations like transabdominal preperitoneal (TAPP) laparoscopic inguinal hernia repair (LIHR) remains unchart...

SAMe: A Semantic Anatomy Mapping Engine for Robotic Ultrasound

Robotic ultrasound has advanced local image-driven control, contact regulation, and view optimization, yet current systems lack the anatomical understanding needed to determine what to scan, where to begin, and how to adapt to individual patient anatomy. These gaps make systems still reliant on expert intervention to initiate scanning. Here we present SAMe, a semantic anatomy mapping engine that p...

SlicerRoboTMS: An Open-Source 3D Slicer Extension for Robot-Assisted Transcranial Magnetic Stimulation

Robot-assisted Transcranial Magnetic Stimulation (Robo-TMS) is an image-guided robotic intervention that enhances the accuracy and reproducibility of ...

Real-time prospective (shadow mode) validation of an AI-based clinical decision support system for predicting 3-month functional outcome in acute stroke: the VALIDATE study protocol

Introduction Despite the proven benefits of reperfusion therapies in acute ischemic stroke, treatment decisions in the hyperacute phase remain complex...

Deep Learning-Guided Holotomography Reveals Early Structural Remodelling During Pluripotency Exit

Real-time assessment of human pluripotent stem cell (hPSC) quality is critical for reproducibility and safety in regenerative medicine, yet current me...

Radiomics- and Clinical Feature-Driven Prediction of Volumetric Response in Skull-Base Meningioma after CyberKnife Radiosurgery

Skull-base meningiomas are often characterized by favorable long-term prognosis, yet their anatomical complexity and proximity to critical neurovascul...

GlioVision: A Multi-Modal MRI Framework for Non-Invasive Glioma Molecular Biomarkers Prediction

Gliomas are aggressive primary brain tumors that necessitate critical molecular biomarker predictions for optimal clinical decision-making. Traditiona...

Prognosis of stroke subtypes in whole population health systems data: a matched cohort study

Background Outcome after stroke varies according to stroke subtype by location, but healthcare systems data studies do not include subtyping informati...

Sum-of-Checks: Structured Reasoning for Surgical Safety with Large Vision-Language Models

Purpose: Accurate assessment of the Critical View of Safety (CVS) during laparoscopic cholecystectomy is essential to prevent bile duct injury, a comp...

Protect the Brain When Treating the Heart: A Convolutional Neural Network for Detecting Emboli

Gaseous microemboli (GME) represent a common complication of cardiac structural interventions across both surgical and transcatheter approaches. Trans...

Analysis and Mitigation of Equipment-induced Shortcuts in AI Models for Laparoscopic Cholecystectomy

Machine learning models have seen a lot of success in medical image segmentation domain. However, one of the challenges that they face are confounders...

SurgCoT: Advancing Spatiotemporal Reasoning in Surgical Videos through a Chain-of-Thought Benchmark

Fine-grained spatiotemporal reasoning on surgical videos is critical, yet the capabilities of Multi-modal Large Language Models (MLLMs) in this domain...

Where are they looking in the operating room?

Purpose: Gaze-following, the task of inferring where individuals are looking, has been widely studied in computer vision, advancing research in visual...

Trustworthy Endoscopic Super-Resolution

Super-resolution (SR) models are attracting growing interest for enhancing minimally invasive surgery and diagnostic videos under hardware constraints...

Can LLM-Generated Text Empower Surgical Vision-Language Pre-training?

Recent advancements in self-supervised learning have led to powerful surgical vision encoders capable of spatiotemporal understanding. However, extend...

Deep learning based Non-Rigid Volume-to-Surface Registration for Brain Shift compensation Using Point Cloud

Soft-tissue deformation remains a major limitation in image-guided neurosurgery, where intra-operative anatomy can deviate substantially from pre-oper...

HyKey: Hyperspectral Keypoint Detection and Matching in Minimally Invasive Surgery

Purpose: 3D reconstruction in minimally invasive surgery (MIS) enables enhanced surgical guidance through improved visualisation, tool tracking, and a...

Preoperative CT-Based Habitat Radiomics Classifiers Predict Recurrence in Non-Small Cell Lung Cancer

Objectives: Among surgically resected non-small cell lung cancer (NSCLC) patients with similar stage and histopathological characteristics, there is v...

Improved Multiscale Structural Mapping with Supervertex Vision Transformer for the Detection of Alzheimer's Disease Neurodegeneration

Alzheimer's disease (AD) confirmation often relies on positron emission tomography (PET) or cerebrospinal fluid (CSF) analysis, which are costly and i...

Towards Patient-Specific Deformable Registration in Laparoscopic Surgery

Unsafe surgical care is a critical health concern, often linked to limitations in surgeon experience, skills, and situational awareness. Integrating p...