AIMC Topic: Craniotomy

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Precise path planning for robot-assisted craniotomy: a CT-driven virtual center method.

Biomedical physics & engineering express
. Craniotomy is a critical prerequisite for numerous neuro-surgeries, including intracranial tumor resection and cerebral hemorrhage decompression. However, conventional manual craniotomy methods are often time-consuming, labor-intensive, and associa...

Comparing supervised machine learning algorithms for the prediction of partial arterial pressure of oxygen during craniotomy.

BMC medical informatics and decision making
BACKGROUND AND OBJECTIVES: Brain tissue oxygenation is usually inferred from arterial partial pressure of oxygen (paO), which is in turn often inferred from pulse oximetry measurements or other non-invasive proxies. Our aim was to evaluate the feasib...

A deep learning approach for objective evaluation of microscopic neuro-drilling craniotomy skills.

Computers in biology and medicine
BACKGROUND: Minimally invasive microscopic and endoscopic neurosurgery demands precise use of high-speed micro-drilling tools to prevent potential complications. Present-day neuro-drilling training methods include cadaveric specimens and surgical sim...

Classification of speech arrests and speech impairments during awake craniotomy: a multi-databases analysis.

International journal of computer assisted radiology and surgery
PURPOSE: Awake craniotomy presents a unique opportunity to map and preserve critical brain functions, particularly speech, during tumor resection. The ability to accurately assess linguistic functions in real-time not only enhances surgical precision...

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

Journal of visualized experiments : JoVE
Cranial window surgery allows for the imaging of brain tissue in live mice with the use of multiphoton or other intravital imaging techniques. However, when performing any craniotomy by hand, there is often thermal damage to brain tissue, which is in...

Three-dimensional deep learning to automatically generate cranial implant geometry.

Scientific reports
We present a 3D deep learning framework that can generate a complete cranial model using a defective one. The Boolean subtraction between these two models generates the geometry of the implant required for surgical reconstruction. There is little or ...

Machine Learning Approaches-Driven for Mortality Prediction for Patients Undergoing Craniotomy in ICU.

Brain injury
OBJECTIVES: We aimed to predict the mortality of patients with craniotomy in ICU by using predictive models to extract the high-risk factors leading to the death of patients from a retrospective a study.

Robotic laser osteotomy through penscriptive structured light visual servoing.

International journal of computer assisted radiology and surgery
PURPOSE: Planning osteotomies is a task that surgeons do as part of standard surgical workflow. This task, however, becomes more difficult and less intuitive when a robot is tasked with performing the osteotomy. In this study, we aim to provide a new...