Neurosurgery

Interpretable Aneurysm Classification via 3D Concept Bottleneck Models: Integrating Morphological and Hemodynamic Clinical Features

We are concerned with the challenge of reliably classifying and assessing intracranial aneurysms usi...

Physics-Based Growth and Remodeling Modeling for Virtual Abdominal Aortic Aneurysm Evolution and Growth Prediction

Computational growth and remodeling (G&R) models have been extentively used to investigate abdominal...

Perspective-Equivariant Fine-tuning for Multispectral Demosaicing without Ground Truth

Multispectral demosaicing is crucial to reconstruct full-resolution spectral images from snapshot mo...

Stable Asynchrony: Variance-Controlled Off-Policy RL for LLMs

Reinforcement learning (RL) is widely used to improve large language models on reasoning tasks, and ...

Hybrid Federated and Split Learning for Privacy Preserving Clinical Prediction and Treatment Optimization

Collaborative clinical decision support is often constrained by governance and privacy rules that pr...

Distributional Deep Learning for Super-Resolution of 4D Flow MRI under Domain Shift

Super-resolution is widely used in medical imaging to enhance low-quality data, reducing scan time a...

Comp2Comp: Open-Source Software with FDA-Cleared Artificial Intelligence Algorithms for Computed Tomography Image Analysis

Artificial intelligence allows automatic extraction of imaging biomarkers from already-acquired radi...

From Pre- to Intra-operative MRI: Predicting Brain Shift in Temporal Lobe Resection for Epilepsy Surgery

Introduction: In neurosurgery, image-guided Neurosurgery Systems (IGNS) highly rely on preoperative ...

Endoleak Prediction After EVAR: A Point Cloud Neural Network Framework Enhanced by Computational Fluid Dynamics and Multi-Features

Background: Endovascular aortic aneurysm repair (EVAR) is effective in preventing rupture of abdomin...

Deep Leakage with Generative Flow Matching Denoiser

Federated Learning (FL) has emerged as a powerful paradigm for decentralized model training, yet it ...

TrackletGPT: A Language-like GPT Framework for White Matter Tract Segmentation

White Matter Tract Segmentation is imperative for studying brain structural connectivity, neurologic...

Portable Biomechanics Laboratory: Clinically Accessible Movement Analysis from a Handheld Smartphone

The way a person moves is a direct reflection of their neurological and musculoskeletal health, ye...

X-RAFT: Cross-Modal Non-Rigid Registration of Blue and White Light Neurosurgical Hyperspectral Images

Integration of hyperspectral imaging into fluorescence-guided neurosurgery has the potential to im...

ClipGS: Clippable Gaussian Splatting for Interactive Cinematic Visualization of Volumetric Medical Data

The visualization of volumetric medical data is crucial for enhancing diagnostic accuracy and impr...

Steps Adaptive Decay DPSGD: Enhancing Performance on Imbalanced Datasets with Differential Privacy with HAM10000

When applying machine learning to medical image classification, data leakage is a critical issue. ...

Intelligent Histology for Tumor Neurosurgery

The importance of rapid and accurate histologic analysis of surgical tissue in the operating room ...

Automated anatomy-based post-processing reduces false positives and improved interpretability of deep learning intracranial aneurysm detection

Introduction: Deep learning (DL) models can help detect intracranial aneurysms on CTA, but high fa...

Introduction. Artificial intelligence in neurosurgery: transforming a data-intensive specialty.

Phenotype-driven risk stratification of cerebral aneurysms using Shapley Additive Explanations-based supervised clustering: a novel approach to rupture prediction.

OBJECTIVE: The aim of this study was to address the limitations of traditional aneurysm risk scoring...

Multitask Deep Learning for Automated Detection of Endoleak at Digital Subtraction Angiography during Endovascular Aneurysm Repair.

Purpose To develop and evaluate a novel multitask deep learning framework for automated detection an...

Methodological Challenges in Deep Learning-Based Detection of Intracranial Aneurysms: A Scoping Review.

Artificial intelligence (AI), particularly deep learning, has demonstrated high diagnostic performan...