Feature extraction from MRI ADC images for brain tumor classification using machine learning techniques
| dc.contributor.author | Vijithananda, Sahan | |
| dc.contributor.author | Jayatilake, Mohan | |
| dc.contributor.author | Hewavithana, Badra | |
| dc.contributor.author | Gonçalves, Teresa | |
| dc.contributor.author | Rato, Luis | |
| dc.contributor.author | Weerakoon, Bimali | |
| dc.contributor.author | Kalupahana, Tharindu | |
| dc.contributor.author | Silva, Anil | |
| dc.contributor.author | Dissanayake, Karuna | |
| dc.date.accessioned | 2023-02-09T16:29:26Z | |
| dc.date.available | 2023-02-09T16:29:26Z | |
| dc.date.issued | 2022-08 | |
| dc.description.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. | por |
| dc.identifier.authoremail | nd | |
| dc.identifier.authoremail | nd | |
| dc.identifier.authoremail | nd | |
| dc.identifier.authoremail | tcg@uevora.pt | |
| dc.identifier.authoremail | lmr@uevora.pt | |
| dc.identifier.authoremail | nd | |
| dc.identifier.authoremail | nd | |
| dc.identifier.authoremail | nd | |
| dc.identifier.authoremail | nd | |
| dc.identifier.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 | por |
| dc.identifier.doi | https://doi.org/10.1186/s12938-022-01022-6 | por |
| dc.identifier.scientificarea | 283 | por |
| dc.identifier.uri | https://doi.org/10.1186/s12938-022-01022-6 | |
| dc.identifier.uri | http://hdl.handle.net/10174/34086 | |
| dc.language.iso | por | por |
| dc.peerreviewed | yes | por |
| dc.publisher | springer Nature | por |
| dc.rights | openAccess | por |
| dc.subject | Images | por |
| dc.subject | Brain tumor classification | por |
| dc.subject | magnetic resonance imaging | por |
| dc.subject | Machine Learning | por |
| dc.subject | Apparent diffusion coefficient | por |
| dc.subject | radiology | por |
| dc.subject | Diffusion weighted imaging | por |
| dc.subject | Random forest | por |
| dc.subject | ANOVA f-test feature selection | por |
| dc.title | Feature extraction from MRI ADC images for brain tumor classification using machine learning techniques | por |
| dc.type | article | por |
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