EconPapers    
Economics at your fingertips  
 

Volumetric Estimation of the Damaged Area in the Human Brain from 2D MR Image

P Naga Srinivasu, T Srinivasa Rao and Valentina Balas
Additional contact information
P Naga Srinivasu: Gitam University, Visakhapatnam, India
T Srinivasa Rao: Gitam University, Visakhapatnam, India

International Journal of Information System Modeling and Design (IJISMD), 2020, vol. 11, issue 1, 74-92

Abstract: In this article, we present a volumetric estimate of the mutilated part in the human brain from a typical 2D MR image that is directly rendered from the scanner, which is first of its kind in the field of medical imaging. The proposed concept necessitates segmentation of the MR image for the identification of dimensions in the damaged region. Once the dimensions are identified from the resultant segmented image, the volume of the damaged region is evaluated through the Gauss Derivation theorem. The pixel to the distance scaling, which is fed as an input for the Gauss Derivation is from an earlier medical diagnosis from another researcher. The proposed algorithm was experimented with real-time images and the obtained results were examined against the real-time scenarios and were observed to exhibit better accuracy.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/IJISMD.2020010105 (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:jismd0:v:11:y:2020:i:1:p:74-92

Access Statistics for this article

International Journal of Information System Modeling and Design (IJISMD) is currently edited by Thierry O. C. Edoh

More articles in International Journal of Information System Modeling and Design (IJISMD) from IGI Global
Bibliographic data for series maintained by Journal Editor ().

 
Page updated 2025-04-19
Handle: RePEc:igg:jismd0:v:11:y:2020:i:1:p:74-92