Robust Brain MRI Segmentation for 3D Printing Applications

Abstract

In this paper, we introduced a technique for efficient simulation, Optimization, and Replication of patient specific procedures and prosthetics for neurosurgery applications the recent advances in computing power and additive manufacturing have made possible. Two important applications are detection and applying additive manufacturing towards brain analogues are in vivo brain modelling and finite element modeling for brain injury simulation. The drawback of efficiently Segmenting imaging data for use in finite element model or 3D printing is still remained. In this, for efficient brain MRI segmentation , we are combining statistically based segmentation with partial differential equation based methods using neuromechanical models, in this we use non-linear filtering, k-mean clustering, active contour modelling techniques for segmentation of brain MRI images. The results of these processes lead us to simulate brain procedures and prosthetics on a patient level using segmented image.

Authors and Affiliations

Chinnapu devi, Shaik Sahera, P. Shivani, Shaik Mazharuddin, N. Madhusudhan

Keywords

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  • EP ID EP23617
  • DOI http://doi.org/10.22214/ijraset.2017.3157
  • Views 340
  • Downloads 7

How To Cite

Chinnapu devi, Shaik Sahera, P. Shivani, Shaik Mazharuddin, N. Madhusudhan (2017). Robust Brain MRI Segmentation for 3D Printing Applications. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 5(3), -. https://europub.co.uk./articles/-A-23617