Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/34086

Title: Feature extraction from MRI ADC images for brain tumor classification using machine learning techniques
Authors: Vijithananda, Sahan
Jayatilake, Mohan
Hewavithana, Badra
Gonçalves, Teresa
Rato, Luis
Weerakoon, Bimali
Kalupahana, Tharindu
Silva, Anil
Dissanayake, Karuna
Keywords: Images
Brain tumor classification
magnetic resonance imaging
Machine Learning
Apparent diffusion coefficient
radiology
Diffusion weighted imaging
Random forest
ANOVA f-test feature selection
Issue Date: Aug-2022
Publisher: springer Nature
Citation: Vijithananda, S.M., Jayatilake, M.L., Hewavithana, B. et al. Feature extraction from MRI ADC images for brain tumor classification using machine learning techniques. BioMed Eng OnLine 21, 52 (2022). https://doi.org/10.1186/s12938-022-01022-6
Abstract: Diffusion-weighted (DW) imaging is a well-recognized magnetic resonance imaging (MRI) technique that is being routinely used in brain examinations in modern clinical radiology practices. This study focuses on extracting demographic and texture features from MRI Apparent Diffusion Coefficient (ADC) images of human brain tumors, identifying the distribution patterns of each feature and applying Machine Learning (ML) techniques to differentiate malignant from benign brain tumors.
URI: https://doi.org/10.1186/s12938-022-01022-6
http://hdl.handle.net/10174/34086
Type: article
Appears in Collections:INF - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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