alexa Precision Robotic-Assisted Implantation for Preclinical Stereotactic Neurosurgery
ISSN: 2168-9873

Journal of Applied Mechanical Engineering
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Review Article

Precision Robotic-Assisted Implantation for Preclinical Stereotactic Neurosurgery

Zheng Liu1, Mojtaba Taherisadr2, Hemmings CH. Wu3, Shiva Abbaszadeh1*

1Dept. of Nuclear, Plasma, and Radiological Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA

2Dept. of Computer and Information Science, University of Michigan, Dearborn, MI, USA

3Dept. of Neurosurgery, Stanford University, 213 Quarry Road, Palo Alto, CA USA 94304-5979

*Corresponding Author:
Abbaszadeh S
Department of Nuclear, Plasma and Radiological Engineering
University of Illinois at Urbana-Champaign, Urbana, IL, USA
Tel: 217-244-9738
E-mail: [email protected]

Received date: June 26, 2017; Accepted date: August 03, 2017; Published date: August 07, 2017

Citation: Liua Z, Taherisadr M, Wu HCH, Abbaszadeh S (2017) Precision Robotic-Assisted Implantation for Preclinical Stereotactic Neurosurgery. J Appl Mech Eng 6:279. doi: 10.4172/2168-9873.1000279

Copyright: © 2017 Abbaszadeh S, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.



During stereotactic neurosurgery procedures, needle insertion or implantation of electrode/cannula/optic fibre requires quick, precise, and accurate identification of insertion location and proper guidance of the needle to accurately reach the target. In this study, we investigate an automated method to locate the entry point of the region of interest. This method leverages a digital image capture system, pattern recognition, and motorized stages. Region-based convolutional neural network and template matching of known anatomical identifiable regions is used to find regions of interest (e.g., Bregma) in rodents.


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