Surgery

Temporomandibular joint and masticatory muscles morphometry and morphology in healthy subjects and individuals with temporomandibular dysfunction: An anatomical, radiological, and machine learning application study.

The study aimed to compare the morphometric and morphologic analyses of the bone structures of temporomandibular joint and masticatory muscles on Cone beam computed tomography (CBCT) in 62 healthy subjects and 33 subjects with temporomandibular dysfunction (TMDS) aged between 18 and 56 years. In addition, a machine learning (ML) pipeline involving the Random Forest classifier was used to automatic...

Intelligent Control of Robotic X-ray Devices using a Language-promptable Digital Twin

Natural language offers a convenient, flexible interface for controlling robotic C-arm X-ray systems, making advanced functionality and controls accessible. However, enabling language interfaces requires specialized AI models that interpret X-ray images to create a semantic representation for reasoning. The fixed outputs of such AI models limit the functionality of language controls. Incorporati...

Graph convolutional networks enable fast hemorrhagic stroke monitoring with electrical impedance tomography

Objective: To develop a fast image reconstruction method for stroke monitoring with electrical impedance tomography with image quality comparable to...

Image Retrieval with Intra-Sweep Representation Learning for Neck Ultrasound Scanning Guidance

Purpose: Intraoperative ultrasound (US) can enhance real-time visualization in transoral robotic surgery. The surgeon creates a mental map with a pr...

RoboMM: All-in-One Multimodal Large Model for Robotic Manipulation

In recent years, robotics has advanced significantly through the integration of larger models and large-scale datasets. However, challenges remain i...

Hyperbolic embedding of brain networks can predict the surgery outcome in temporal lobe epilepsy

Epilepsy surgery, particularly for temporal lobe epilepsy (TLE), remains a vital treatment option for patients with drug-resistant seizures. However...

Adaptive Graph Learning from Spatial Information for Surgical Workflow Anticipation

Surgical workflow anticipation is the task of predicting the timing of relevant surgical events from live video data, which is critical in Robotic-A...

A Combined Channel Approach for Decoding Intracranial EEG Signals: Enhancing Accuracy through Spatial Information Integration

Intracranial EEG (iEEG) recording, characterized by high spatial and temporal resolution and superior signal-to-noise ratio (SNR), enables the devel...

[A pilot study on clinical application of three-dimensional morphological completion of lesioned mandibles assisted by generative adversarial networks].

To explore the clinical application pathway of the CT generative adversarial networks (CTGANs) algorithm in mandibular reconstruction surgery, aiming...

SurgBox: Agent-Driven Operating Room Sandbox with Surgery Copilot

Surgical interventions, particularly in neurology, represent complex and high-stakes scenarios that impose substantial cognitive burdens on surgical...

Benchmarking and Enhancing Surgical Phase Recognition Models for Robotic-Assisted Esophagectomy

Robotic-assisted minimally invasive esophagectomy (RAMIE) is a recognized treatment for esophageal cancer, offering better patient outcomes compared...

MT3DNet: Multi-Task learning Network for 3D Surgical Scene Reconstruction

In image-assisted minimally invasive surgeries (MIS), understanding surgical scenes is vital for real-time feedback to surgeons, skill evaluation, a...

Electrocardiogram-based diagnosis of liver diseases: an externally validated and explainable machine learning approach

Background: Liver diseases present a significant global health challenge and often require costly, invasive diagnostics. Electrocardiography (ECG), ...

Interpretable Hierarchical Attention Network for Medical Condition Identification

Accurate prediction of medical conditions with straight past clinical evidence is a long-sought topic in the medical management and health insurance...

Benchmarking Pretrained Attention-based Models for Real-Time Recognition in Robot-Assisted Esophagectomy

Esophageal cancer is among the most common types of cancer worldwide. It is traditionally treated using open esophagectomy, but in recent years, rob...

Haptic Stiffness Perception Using Hand Exoskeletons in Tactile Robotic Telemanipulation

Robotic telemanipulation - the human-guided manipulation of remote objects - plays a pivotal role in several applications, from healthcare to operat...

Active learning of neural population dynamics using two-photon holographic optogenetics

Recent advances in techniques for monitoring and perturbing neural populations have greatly enhanced our ability to study circuits in the brain. In ...

SimuScope: Realistic Endoscopic Synthetic Dataset Generation through Surgical Simulation and Diffusion Models

Computer-assisted surgical (CAS) systems enhance surgical execution and outcomes by providing advanced support to surgeons. These systems often rely...

SparseGrasp: Robotic Grasping via 3D Semantic Gaussian Splatting from Sparse Multi-View RGB Images

Language-guided robotic grasping is a rapidly advancing field where robots are instructed using human language to grasp specific objects. However, e...

A Novel Generative Multi-Task Representation Learning Approach for Predicting Postoperative Complications in Cardiac Surgery Patients

Early detection of surgical complications allows for timely therapy and proactive risk mitigation. Machine learning (ML) can be leveraged to identif...