Neurosurgery

Real-time simulation of viscoelastic tissue behavior with physics-guided deep learning.

Finite element methods (FEM) are popular approaches for simulation of soft tissues with elastic or viscoelastic behavior. However, their usage in real-time applications, such as in virtual reality surgical training, is limited by computational cost. In this application scenario, which typically involves transportable simulators, the computing hardware severely constrains the size or the level of d...

A review on tissue-needle interaction and path planning models for bevel tip type flexible needle minimal intervention.

A flexible needle has emerged as a crucial clinical technique in contemporary medical practices, particularly for minimally invasive interventions. Its applicability spans diverse surgical domains such as brachytherapy, cardiovascular surgery, neurosurgery and others. Notably, flexible needles find utility in biopsies requiring deep skin penetration to access infected areas. Despite its minimally ...

Neurosurgery inpatient outcome prediction for discharge planning with deep learning and transfer learning.

INTRODUCTION: Deep learning may be able to assist with the prediction of neurosurgical inpatient outcomes. The aims of this study were to investigate ...

Machine learning for outcome prediction of neurosurgical aneurysm treatment: Current methods and future directions.

INTRODUCTION: Machine learning algorithms have received increased attention in neurosurgical literature for improved accuracy over traditional predict...

Clipped DeepControl: Deep neural network two-dimensional pulse design with an amplitude constraint layer.

Advanced radio-frequency pulse design used in magnetic resonance imaging has recently been demonstrated with deep learning of (convolutional) neural n...

Detection of cerebral aneurysms using artificial intelligence: a systematic review and meta-analysis.

BACKGROUND: Subarachnoid hemorrhage from cerebral aneurysm rupture is a major cause of morbidity and mortality. Early aneurysm identification, aided b...

Robot-Assisted Surgery of an Iliac Artery Aneurysm: A Case Report.

Robot-assisted surgery has not yet been able to establish itself for vascular surgery. However, the preconditions for robot-assisted vascular interven...

Assessment of Thermal Damage from Robot-Drilled Craniotomy for Cranial Window Surgery in Mice.

Cranial window surgery allows for the imaging of brain tissue in live mice with the use of multiphoton or other intravital imaging techniques. However...

Successful implementation of a nurse-navigator-run program using natural language processing identifying patients with an abdominal aortic aneurysm.

BACKGROUND: Abdominal aortic aneurysms (AAA) are often identified incidentally on imaging studies. Patients and/or providers are frequently unaware of...

Modular robotic platform for precision neurosurgery with a bio-inspired needle: System overview and first in-vivo deployment.

Over the past 10 years, minimally invasive surgery (MIS) has shown significant benefits compared to conventional surgical techniques, with reduced tra...

Detection of intracranial aneurysms using deep learning-based CAD system: usefulness of the scores of CNN's final layer for distinguishing between aneurysm and infundibular dilatation.

PURPOSE: We evaluated the diagnostic performance of a clinically available deep learning-based computer-assisted diagnosis software for detecting unru...

Comparison of Deep Learning and Classical Machine Learning Algorithms to Predict Postoperative Outcomes for Anterior Cervical Discectomy and Fusion Procedures With State-of-the-art Performance.

STUDY DESIGN: Retrospective cohort.

Answer to the letter to the editor by Zhi-Hui Dai concerning "Artificial intelligence in predicting early-onset adjacent segment degeneration following anterior cervical discectomy and fusion" by Rudisill SS et al. (Eur Spine J [2022]; doi: 10.1007/s00586-022-07238-3).

Targeting the Future: Developing a Training Curriculum for Robotic Assisted Neurosurgery.

OBJECTIVE: Technological advances have significantly fostered the use of robotics in neurosurgery. Due to their novelty, there is a need to develop tr...

Letter to the Editor concerning "Artificial intelligence in predicting early-onset adjacent segment degeneration following anterior cervical discectomy and fusion" by Rudisill SS, et al. (Eur Spine J [2022]; doi: 10.1007/s00586-022-07238-3).

DSA Image Analysis of Clinical Features and Nursing Care of Cerebral Aneurysm Patients Based on the Deep Learning Algorithm.

OBJECTIVE: A deep learning algorithm was developed for automatic detection and localization of intracranial aneurysms in DSA, and its clinical charact...

One-step Endovascular Aortic Aneurysm Repair With CO2 contrast and Robotic Partial Nephrectomy for Renal Cell Carcinoma: Case Report.

INTRODUCTION: Although rare, as the population ages, abdominal aortic aneurysm synchronous to abdominal malignancies, as renal cell carcinoma, is expe...

Adaptive wireless millirobotic locomotion into distal vasculature.

Microcatheters have enabled diverse minimally invasive endovascular operations and notable health benefits compared with open surgeries. However, with...

Performance of deep learning in the detection of intracranial aneurysm: A systematic review and meta-analysis.

PURPOSE: Early detection and diagnosis of intracranial aneurysms (IAs) are particularly critical. Deep learning models (DLMs) are now widely used in t...

A deep learning-based automatic system for intracranial aneurysms diagnosis on three-dimensional digital subtraction angiographic images.

BACKGROUND: Intracranial aneurysms (IAs) are a life-threatening disease. Their rupture can lead to hemorrhagic stroke. Most studies applying deep lear...