2019
DOI: 10.21833/ijaas.2019.07.012
|View full text |Cite
|
Sign up to set email alerts
|

Enhanced feature extraction technique for brain MRI classification based on Haar wavelet and statistical moments

Abstract: Many methods have been proposed to classify the MR brain images automatically. We have proposed a method based on a Neural Network (NN) to classify the normality and abnormality of a given MR brain image. This method first employs a median filter to minimize the noise from the image and converted the image to RGB. Then applies the technique of Discrete Wavelet Transform (DWT) to extract the important features from the image and color moments have been employed in the feature reduction stage to reduce the dimen… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
18
0
1

Year Published

2019
2019
2023
2023

Publication Types

Select...
8
1

Relationship

1
8

Authors

Journals

citations
Cited by 19 publications
(19 citation statements)
references
References 20 publications
0
18
0
1
Order By: Relevance
“…In addition, the simplicity of this type of wavelet computationally reduces operations compared to other types and increases the learning speed of the network. 26 The basis of the wavelet transform work is that it passes the signals through the high-pass and low-pass filters and performs the decomposition step by step. Each step involves a filter and then a downsampler.…”
Section: Methodsmentioning
confidence: 99%
“…In addition, the simplicity of this type of wavelet computationally reduces operations compared to other types and increases the learning speed of the network. 26 The basis of the wavelet transform work is that it passes the signals through the high-pass and low-pass filters and performs the decomposition step by step. Each step involves a filter and then a downsampler.…”
Section: Methodsmentioning
confidence: 99%
“…These should be texts that can be classified under a given genre and/or written by the same author. K-means clustering, one of the simplest and most popular cluster analysis methods, is used for the task [73][74][75]. In this process, every data point (the novels in our case) is assigned to the closest center or nearest mean based on their Euclidean distance.…”
Section: Discussionmentioning
confidence: 99%
“…Statistical moments have been employed for feature extraction, and ANN has been used for feature reduction. Zahid et al [43] proposed another methodology for brain MRI classification using DWT, color moments, and ANN. The DWT method has been used for image decomposition and removed low detail from the image to obtain an approximate small-sized image.…”
Section: Related Workmentioning
confidence: 99%