Latest AI and machine learning research in neurosurgery for healthcare professionals.
PURPOSE: Although segmentation of Abdominal Aortic Aneurysms (AAA) thrombus is a crucial step for both the planning of endovascular treatment and the monitoring of the intervention's outcome, it is still performed manually implying time consuming operations as well as operator dependency. The present paper proposes a fully automatic pipeline to segment the intraluminal thrombus in AAA from contras...
In recent years, due to the simple design idea and good recognition effect, deep learning method has attracted more and more researchers' attention in computer vision tasks. Aiming at the problem of athlete behavior recognition in mass sports teaching video, this paper takes depth video as the research object and cuts the frame sequence as the input of depth neural network model, inspired by the s...
Vision loss happens due to diabetic retinopathy (DR) in severe stages. Thus, an automatic detection method applied to diagnose DR in an earlier phase ...
Efficiently implementing remote sensing image classification with high spatial resolution imagery can provide significant value in land use and land c...
Enlargement or aneurysm of the aorta predisposes to dissection, an important cause of sudden death. We trained a deep learning model to evaluate the d...
With the continuous development of information technology, robotics and data science will certainly have a similar impact on invasive medicine over th...
The field of vascular surgery is constantly evolving and is unsurpassed in its innovation and adoption of new technologies. Endovascular therapy has f...
Subarachnoid hemorrhage (SAH) is a serious cerebrovascular disease with a high mortality rate and is known as a disease that is hard to diagnose becau...
BACKGROUND: Fine operation has been an eternal topic in neurosurgery. There were many problems in functional neurosurgery field with high precision re...
PURPOSE: For the planning and navigation of neurosurgery, we have developed a fully convolutional network (FCN)-based method for brain structure segme...
Artificial intelligence (AI) is a branch of computer science with a variety of subfields and techniques, exploited to serve as a deductive tool that p...
OBJECTIVE: The aim of this study was to evaluate an automatic, deep learning based method (Augmented Radiology for Vascular Aneurysm [ARVA]), to detec...
It remains difficult to predict when which patients with abdominal aortic aneurysm (AAA) will require surgery. The aim was to study the accuracy of ge...
Machine learning is a rapidly evolving field that offers physicians an innovative and comprehensive mechanism to examine various aspects of patient da...
The study aims to explore the application of international classification of diseases (ICD) coding technology and embedded electronic medical record (...
The simultaneous growth of robotic-assisted surgery and telemedicine in recent years has only been accelerated by the recent coronavirus disease 2019 ...
OBJECT: The purpose of this review is to highlight the major factors limiting the progress of robotics development in the field of cranial neurosurger...
INTRODUCTION: The treatment of renal artery aneurysms (RAAs) includes surgical repair and endovascular techniques. Surgical repair is divided into ope...
BACKGROUND AND OBJECTIVE: The decompressive laminectomy is one of the most common operations to treat lumbar spinal stenosis by removing the laminae a...
INTRODUCTION: Electrode array translocation is an unpredictable event with all types of arrays, even using a teleoperated robot in a clinical scenario...