Medical image classification using MRI: An investigation

Title

Medical image classification using MRI: An investigation

Creator

Merjulah R.; Chandra J.

Description

The main objective of the paper is to review the performance of various machine learning classification technique currently used for magnetic resonance imaging. The prerequisite for the best classification technique is the main drive for the paper. In magnetic resonance imaging, detection of various diseases might be simple but the physicians need quantification for further treatment. So, the machine learning along with digital image processing aids for the diagnosis of the diseases and synergizes between the computer and the radiologist. The review of machine learning classification based on the support vector machine, discrete wavelet transform, artificial neural network, and principal component analysis reveals that discrete wavelet transform combined with other highly used method like PCA, ANN, etc., will bring high accuracy rate of 100%. The hybrid technique provides the second opinion to the radiologist on taking the decision. Springer Nature Switzerland AG 2019.

Source

Lecture Notes in Computational Vision and Biomechanics, Vol-30, pp. 1135-1146.

Date

2019-01-01

Publisher

Springer Netherlands

Subject

Artificial neural network (ANN); Discrete wavelet transform (DWT); Magnetic resonance imaging (MRI); Principal component analysis (PCA); Support vector machine (SVM)

Coverage

Merjulah R., Christ University, Bangalore, India; Chandra J., Christ University, Bangalore, India

Rights

Restricted Access

Relation

ISSN: 22129391

Format

Online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.1007/978-3-030-00665-5_108

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060224036&doi=10.1007%2f978-3-030-00665-5_108&partnerID=40&md5=6c173a10c50ee10311f152d8a2c9e7fe