Neurosurgery

4D-CTA Image and geometry dataset for kinematic analysis of abdominal aortic aneurysms

This article presents a dataset used in the article "Kinematics of Abdominal Aortic Aneurysms", published in the Journal of Biomechanics. The dataset is publicly available for download from the Zenodo data repository (https://doi.org/10.5281/zenodo.15477710). The dataset includes time-resolved 3D computed tomography angiography (4D-CTA) images of abdominal aortic aneurysm (AAA) captured througho...

4D-CTA Image and geometry dataset for kinematic analysis of abdominal aortic aneurysms

This article presents a dataset used in the article "Kinematics of Abdominal Aortic Aneurysms" [arXiv:2405.13377], published in the Journal of Biomechanics. The dataset is publicly available for download from the Zenodo data repository (https://doi.org/10.5281/zenodo.15477710). The dataset includes time-resolved 3D computed tomography angiography (4D-CTA) images of abdominal aortic aneurysm (AAA...

Machine learning for clinical outcome prediction in cerebrovascular and endovascular neurosurgery: systematic review and meta-analysis.

BACKGROUND: Machine learning (ML) may be superior to traditional methods for clinical outcome prediction. We sought to systematically review the liter...

Aneumo: A Large-Scale Multimodal Aneurysm Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks

Intracranial aneurysms (IAs) are serious cerebrovascular lesions found in approximately 5\% of the general population. Their rupture may lead to hig...

Fine-tuning Quantized Neural Networks with Zeroth-order Optimization

As the size of large language models grows exponentially, GPU memory has become a bottleneck for adapting these models to downstream tasks. In this ...

PMQ-VE: Progressive Multi-Frame Quantization for Video Enhancement

Multi-frame video enhancement tasks aim to improve the spatial and temporal resolution and quality of video sequences by leveraging temporal informa...

A Training Framework for Optimal and Stable Training of Polynomial Neural Networks

By replacing standard non-linearities with polynomial activations, Polynomial Neural Networks (PNNs) are pivotal for applications such as privacy-pr...

Two-Stage Generative Model for Intracranial Aneurysm Meshes with Morphological Marker Conditioning

A generative model for the mesh geometry of intracranial aneurysms (IA) is crucial for training networks to predict blood flow forces in real time, ...

A fully automatic radiomics pipeline for postoperative facial nerve function prediction of vestibular schwannoma.

Vestibular schwannoma (VS) is the most prevalent intracranial schwannoma. Surgery is one of the options for the treatment of VS, with the preservation...

Current Trends and Future Directions in Lumbar Spine Surgery: A Review of Emerging Techniques and Evolving Management Paradigms.

: Lumbar spine surgery has undergone significant technological transformation in recent years, driven by the goals of minimizing invasiveness, improvi...

Automatic CTA analysis for blood vessels and aneurysm features extraction in EVAR planning.

Endovascular Aneurysm Repair (EVAR) is a minimally invasive procedure crucial for treating abdominal aortic aneurysms (AAA), where precise pre-operati...

Promptable segmentation of CT lung lesions based on improved U-Net and Segment Anything model (SAM).

BackgroundComputed tomography (CT) is widely used in clinical diagnosis of lung diseases. The automatic segmentation of lesions in CT images aids in t...

AI-Driven Advances in Parkinson's Disease Neurosurgery: Enhancing Patient Selection, Trial Efficiency, and Therapeutic Outcomes.

Parkinson's disease (PD) is a progressive neurodegenerative disorder marked by motor and non-motor dysfunctions that severely compromise patients' qua...

CFD-Based Quantification of Hemodynamic Variables in Cerebral Aneurysms: How Hemodynamics Shape Aneurysm Fate

Cerebral aneurysms are pathological dilations of intracranial arteries that can rupture with devastating consequences, including subarachnoid hemorr...

Development and Validation of a Sham-AI Model for Intracranial Aneurysm Detection at CT Angiography.

Purpose To evaluate a sham-artificial intelligence (AI) model acting as a placebo control for a standard-AI model for diagnosis of intracranial aneury...

Battle of the authors: Comparing neurosurgery articles written by humans and AI.

BACKGROUND: The advancement of artificial intelligence (AI) has led to its application in various fields, including medical literature. This study com...

FGMP: Fine-Grained Mixed-Precision Weight and Activation Quantization for Hardware-Accelerated LLM Inference

Quantization is a powerful tool to improve large language model (LLM) inference efficiency by utilizing more energy-efficient low-precision datapath...

CDUPatch: Color-Driven Universal Adversarial Patch Attack for Dual-Modal Visible-Infrared Detectors

Adversarial patches are widely used to evaluate the robustness of object detection systems in real-world scenarios. These patches were initially des...

Hemodynamic Markers: CFD-Based Prediction of Cerebral Aneurysm Rupture Risk

This study investigates the influence of aneurysm evolution on hemodynamic characteristics within the sac region. Using computational fluid dynamics...

DC-SGD: Differentially Private SGD with Dynamic Clipping through Gradient Norm Distribution Estimation

Differentially Private Stochastic Gradient Descent (DP-SGD) is a widely adopted technique for privacy-preserving deep learning. A critical challenge...