A Comparative Objective Assessment on Mesh-Based and SVM-Based 3D Reconstruction of MRI Brain

Sushitha Susan Joseph and Aju D.
Additional contact information
Sushitha Susan Joseph: Vellore Institute of Technology, Vellore, India
Aju D.: Vellore Institute of Technology, Vellore, India

International Journal of Natural Computing Research (IJNCR), 2019, vol. 8, issue 3, 41-54

Abstract: Three-dimensional reconstruction is the process of acquiring the volumetric information from two dimensions, converting and representing it in three dimensions. The reconstructed images play a vital role in the disease diagnosis, treatment and surgery. Brain surgery is one of the main treatment options following the diagnosis of brain damage. The risk associated with brain surgery is high. Reconstructed brain images help the surgeons to visualize the exact location of tumor, plan and perform the surgical procedures from craniotomy to tumor resection with high precision. This survey provides an overview of the three-dimensional reconstruction techniques in MRI brain and brain tumors. The triangle generation methods and support vector machine methods are briefly described. The advantages and disadvantages of each method is discussed. The comparison reveals that Immune Sphere Shaped Support Vector Machine is the best choice when execution time is considered and triangle mesh generation algorithm is the best when visual quality is considered.

Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/IJNCR.2019070103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jncr00:v:8:y:2019:i:3:p:41-54

Access Statistics for this article

International Journal of Natural Computing Research (IJNCR) is currently edited by Xuewen Xia

More articles in International Journal of Natural Computing Research (IJNCR) from IGI Global
Bibliographic data for series maintained by Journal Editor ().