An Efficient Gabor Walsh-Hadamard Transform Based Approach for Retrieving Brain Tumor Images From MRI

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F21%3A50018294" target="_blank" >RIV/62690094:18470/21:50018294 - isvavai.cz</a>

Result on the web

<a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9521518" target="_blank" >https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9521518</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ACCESS.2021.3107371" target="_blank" >10.1109/ACCESS.2021.3107371</a>

Result language

angličtina

Original language name

An Efficient Gabor Walsh-Hadamard Transform Based Approach for Retrieving Brain Tumor Images From MRI

Original language description

Brain tumors are a serious and death-defying disease for human life. Discovering an appropriate brain tumor image from a magnetic resonance imaging (MRI) archive is a challenging job for the radiologist. Most search engines retrieve images on the basis of traditional text-based approaches. The main challenge in the MRI image analysis is that low-level visual information captured by the MRI machine and the high-level information identified by the assessor. This semantic gap is addressed in this study by designing a new feature extraction technique. In this paper, we introduce Content-Based Medical Image retrieval (CBMIR) system for retrieval of brain tumor images from the large data. Firstly, we remove noise from MRI images employing several filtering techniques. Afterward, we design a feature extraction scheme combining Gabor filtering technique (which is mainly focused on specific frequency content at the image region) and Walsh-Hadamard transform (WHT) (conquer technique for easy configuration of image) for discovering representative features from MRI images. After that, for retrieving the accurate and reliable image, we employ Fuzzy C-Means clustering Minkowski distance metric that can evaluate the similarity between the query image and database images. The proposed methodology design was tested on a publicly available brain tumor MRI image database. The experimental results demonstrate that our proposed approach outperforms most of the existing techniques like Gabor, wavelet, and Hough transform in detecting brain tumors and also take less time. The proposed approach will be beneficial for radiologists and also for technologists to build an automatic decision support system that will produce reproducible and objective results with high accuracy.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

IEEE Access

ISSN

2169-3536

e-ISSN

—

Volume of the periodical

9

Issue of the periodical within the volume

August

Country of publishing house

US - UNITED STATES

Number of pages

12

Pages from-to

119078-119089

UT code for WoS article

000692174600001

EID of the result in the Scopus database

2-s2.0-85113902252