PROJECT TITLE :

Review of Robotic Technology for Stereotactic Neurosurgery

ABSTRACT:

The research of stereotactic apparatus to guide surgical devices began in 1908, yet a significant half of nowadays's stereotactic neurosurgeries still depend on stereotactic frames developed nearly 0.5 a century ago. Robots excel at handling spatial data, and are, therefore, obvious candidates in the guidance of instrumentation along exactly planned trajectories. During this review, we have a tendency to introduce the concept of stereotaxy and describe a customary stereotactic neurosurgery. Neurosurgeons' expectations and demands relating to the role of robots as assistive tools are addressed. We tend to list the most successful robotic systems developed specifically for or capable of executing stereotactic neurosurgery. A critical review is presented for every robotic system, emphasizing the differences between them and detailing positive options and drawbacks. An analysis of the listed robotic system options is additionally undertaken, within the context of robotic application in stereotactic neurosurgery. Finally, we have a tendency to discuss the present perspective, and future directions of a robotic technology during this field. All robotic systems follow a terribly similar and structured workflow despite the technical differences that set them apart. No system unequivocally stands out as an best possible. The trend of technological progress is pointing toward the event of miniaturized value-effective solutions with more intuitive interfaces.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE : Revisiting Light Field Rendering with Deep Anti-Aliasing Neural Network ABSTRACT: The reconstruction of the light field (LF) is primarily hindered by two obstacles: a large disparity and the effect of not following
PROJECT TITLE : Deep Generative Modelling A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models ABSTRACT: Deep generative models are a category of methods that train deep neural networks
PROJECT TITLE : A Comprehensive Review of Computing Paradigms, Enabling Computation Offloading and Task Execution in Vehicular Networks ABSTRACT: The research community focused on vehicle networking has always placed a primary
PROJECT TITLE : An Empirical Review of Deep Learning Frameworks for Change Detection Model Design, Experimental Frameworks, Challenges and Research Needs ABSTRACT: One of the fundamental objectives of computer vision and video
PROJECT TITLE : A Review for Weighted MinHash Algorithms ABSTRACT: The computation of data similarity, also known as data distance, is a fundamental research topic that serves as the basis for a large number of high-level applications

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry