Neurosurgery

Beyond Aortic Diameter for the Management of Thoracic Aortic Aneurysm: Multidimensional Data for Multidisciplinary Discussion.

Thoracic Aortic Aneurysm Risk Assessment: A Machine Learning Approach.

BACKGROUND: Traditional methods of risk assessment for thoracic aortic aneurysm (TAA) based on aneurysm size alone have been called into question as being unreliable in predicting complications. Biomechanical function of aortic tissue may be a better predictor of risk, but it is difficult to determine in vivo.

Using robotics to move a neurosurgeon's hands to the tip of their endoscope.

A major advantage of surgical robots is that they can reduce the invasiveness of a procedure by enabling the clinician to manipulate tools as they wou...

A state-of-the-art review on deep learning for estimating eloquent cortex from resting-state fMRI.

Deep learning algorithms have greatly improved our ability to estimate eloquent cortex regions from resting-state brain scans for patients about to un...

A Deep Learning Model for Automatic Segmentation of Intraparenchymal and Intraventricular Hemorrhage for Catheter Puncture Path Planning.

Intracerebral hemorrhage is the subtype of stroke with the highest mortality rate, especially when it also causes secondary intraventricular hemorrhag...

Comparison of 1.5 T and 3 T magnetic resonance angiography for detecting cerebral aneurysms using deep learning-based computer-assisted detection software.

PURPOSE: To compare the diagnostic performance of 1.5 T versus 3 T magnetic resonance angiography (MRA) for detecting cerebral aneurysms with clinical...

Neuroendoscopy-Assisted Minimal Invasive Management of Chiari 1 Malformation.

 The aim this study is to present the results of the minimal invasive neuroendoscopic-assisted system application as an alternative to traditional su...

Robotic Interventional Neuroradiology: Progress, Challenges, and Future Prospects.

Advances in robotic technology have improved standard techniques in numerous surgical and endovascular specialties, offering more precision, control, ...

A systematic review on intracranial aneurysm and hemorrhage detection using machine learning and deep learning techniques.

The risk of discovering an intracranial aneurysm during the initial screening and follow-up screening are reported as around 11%, and 7% respectively ...

Single-Port Robotic Removal of a Submucosal Foreign Body in the Distal Hypopharynx.

In this report, we present a 55-year-old female with cervical stenosis that underwent C5-C7 anterior cervical discectomy and fusion surgery complicate...

Surgical Robotics for Intracerebral Hemorrhage Treatment: State of the Art and Future Directions.

Intracerebral hemorrhage (ICH) is a stroke subtype with high mortality and disability, and there are no proven medical treatments that can improve the...

Identification of milling status based on vibration signals using artificial intelligence in robot-assisted cervical laminectomy.

BACKGROUND: With advances in science and technology, the application of artificial intelligence in medicine has significantly progressed. The purpose ...

A comparison of performance between a deep learning model with residents for localization and classification of intracranial hemorrhage.

Intracranial hemorrhage (ICH) from traumatic brain injury (TBI) requires prompt radiological investigation and recognition by physicians. Computed tom...

Bidirectional feature matching based on deep pairwise contrastive learning for multiparametric MRI image synthesis.

Multi-parametric MR image synthesis is an effective approach for several clinical applications where specific modalities may be unavailable to reach a...

Tool-tissue force segmentation and pattern recognition for evaluating neurosurgical performance.

Surgical data quantification and comprehension expose subtle patterns in tasks and performance. Enabling surgical devices with artificial intelligence...

The clinical application of neuro-robot in the resection of epileptic foci: a novel method assisting epilepsy surgery.

During surgery for foci-related epilepsy, neurosurgeons face significant difficulties in identifying and resecting MRI-negative or deep-seated epilept...

USING CONVOLUTIONAL NEURAL NETWORK-BASED SEGMENTATION FOR IMAGE-BASED COMPUTATIONAL FLUID DYNAMICS SIMULATIONS OF BRAIN ANEURYSMS: INITIAL EXPERIENCE IN AUTOMATED MODEL CREATION.

"Image-based" computational fluid dynamics (CFD) simulations provide insights into each patient's hemodynamic environment. However, current standard p...

Measurement of interspinous motion in dynamic cervical radiographs using a deep learning-based segmentation model.

OBJECTIVE: Interspinous motion (ISM) is a representative method for evaluating the functional fusion status following anterior cervical discectomy and...

Artificial Intelligence (AI) in Neurosurgery: Information Management and Administrative Burden Solutions.

Neurosurgical skills analysis by machine learning models: systematic review.

Machine learning (ML) models are being actively used in modern medicine, including neurosurgery. This study aimed to summarize the current application...