ON-Line MRI image selection and tumor classification using artificial neural network

Author

Ahmad, Ahmad Shihab

Source

Ibn al-Haitham Journal for Pure and Applied Science

Issue

Vol. 33, Issue 1 (30 Apr. 2020), pp.162-172, 11 p.

Publisher

University of Baghdad College of Education for Pure Science / Ibn al-Haitham

Publication Date

2020-04-30

Country of Publication

Iraq

No. of Pages

11

Main Topic

Nursing

Abstract EN

When soft tissue planning is important, usually, the Magnetic Resonance Imaging (MRI) is a medical imaging technique of selection. In this work, we show a modern method for automated diagnosis depending on a magnetic resonance images classification of the MRI. The presented technique has two main stages; features extraction and classification. We obtained the features corresponding to MRI images implementing Discrete Wavelet Transformation (DWT), inverse and forward, and textural properties, like rotation invariant texture features based on Gabor filtering, and evaluate the meaning of every property in the classification. The classifier is according to Feed Forward Back Propagation Artificial Neural Network (FP-ANN) in the classification stage. The properties thereafter derived to be implemented to teach a neural network based binary classifier that will be automatically able to conclude whether the image is that of a pathological, suffering from brain lesion, or a normal brain. The proposed algorithm obtained the sensitivity of 97.50%, specificity of 82.86% and accuracy of 94.3% for clinical Brain MRI database. This outcome proofs that the presented algorithm is robust and effective compared with other recent techniques.

American Psychological Association (APA)

Ahmad, Ahmad Shihab. 2020. ON-Line MRI image selection and tumor classification using artificial neural network. Ibn al-Haitham Journal for Pure and Applied Science،Vol. 33, no. 1, pp.162-172.
https://search.emarefa.net/detail/BIM-947411

Modern Language Association (MLA)

Ahmad, Ahmad Shihab. ON-Line MRI image selection and tumor classification using artificial neural network. Ibn al-Haitham Journal for Pure and Applied Science Vol. 33, no. 1 (2020), pp.162-172.
https://search.emarefa.net/detail/BIM-947411

American Medical Association (AMA)

Ahmad, Ahmad Shihab. ON-Line MRI image selection and tumor classification using artificial neural network. Ibn al-Haitham Journal for Pure and Applied Science. 2020. Vol. 33, no. 1, pp.162-172.
https://search.emarefa.net/detail/BIM-947411

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 171-172

Record ID

BIM-947411