Next Article in Journal
Accelerated Detector Response Function in Squeezed Vacuum
Next Article in Special Issue
A Novel Kernel-Based Regularization Technique for PET Image Reconstruction
Previous Article in Journal
Overhanging Features and the SLM/DMLS Residual Stresses Problem: Review and Future Research Need
Previous Article in Special Issue
Wireless Accelerometer for Neonatal MRI Motion Artifact Correction
Article Menu
Issue 2 (June) cover image

Export Article

Open AccessReview
Technologies 2017, 5(2), 16; doi:10.3390/technologies5020016

Review of Computational Methods on Brain Symmetric and Asymmetric Analysis from Neuroimaging Techniques

1
Department of Computer Science and Applications, Gandhigram Rural Institute, Deemed University, Gandhigram, 624 302 Tamil Nadu, India
2
Computational Imaging and VisAnalysis (CIVA) Lab, Department of Computer Science, University of Missouri-Columbia, Columbia, MO 65211, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Yudong Zhang and Zhengchao Dong
Received: 26 November 2016 / Revised: 16 April 2017 / Accepted: 17 April 2017 / Published: 18 April 2017
(This article belongs to the Special Issue Medical Imaging & Image Processing Ⅱ)
View Full-Text   |   Download PDF [492 KB, uploaded 18 April 2017]   |  

Abstract

The brain is the most complex organ in the human body and it is divided into two hemispheres—left and right. The left hemisphere is responsible for control of the right side of our body, whereas the right hemisphere is responsible for control of the left side of our body. Brain image segmentation from different neuroimaging modalities is one of the important parts of clinical diagnostic tools. Neuroimaging based digital imagery generally contain noise, inhomogeneity, aliasing artifacts, and orientational deviations. Therefore, accurate segmentation of brain images is a very difficult task. However, the development of accurate segmentation of brain images is very important and crucial for a correct diagnosis of any brain related diseases. One of the fundamental segmentation tasks is to identify and segment inter-hemispheric fissure/mid-sagittal planes, which separate the two hemispheres of the brain. Moreover, the symmetric/asymmetric analyses of left and right hemispheres of brain structures are important for radiologists to analyze diseases such as Alzheimer’s, autism, schizophrenia, lesions and epilepsy. Therefore, in this paper, we have analyzed the existing computational techniques used to find brain symmetric/asymmetric analysis in different neuroimaging techniques such as the magnetic resonance (MR), computed tomography (CT), positron emission tomography (PET), single-photon emission computed tomography (SPECT), which are utilized for detecting various brain related disorders. View Full-Text
Keywords: computational imaging; midsagittal plane; inter-hemispheric fissure; symmetry analysis; neuroimaging computational imaging; midsagittal plane; inter-hemispheric fissure; symmetry analysis; neuroimaging
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Kalavathi, P.; Senthamilselvi, M.; Prasath, V.B.S. Review of Computational Methods on Brain Symmetric and Asymmetric Analysis from Neuroimaging Techniques. Technologies 2017, 5, 16.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Technologies EISSN 2227-7080 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top