Cargando…
Application of Machine Learning Techniques for Characterization of Ischemic Stroke with MRI Images: A Review
Magnetic resonance imaging (MRI) is a standard tool for the diagnosis of stroke, but its manual interpretation by experts is arduous and time-consuming. Thus, there is a need for computer-aided-diagnosis (CAD) models for the automatic segmentation and classification of stroke on brain MRI. The heter...
Autores principales: | Subudhi, Asit, Dash, Pratyusa, Mohapatra, Manoranjan, Tan, Ru-San, Acharya, U. Rajendra, Sabut, Sukanta |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9600234/ https://www.ncbi.nlm.nih.gov/pubmed/36292224 http://dx.doi.org/10.3390/diagnostics12102535 |
Ejemplares similares
-
Deep Transfer Learning for Automatic Prediction of Hemorrhagic Stroke on CT Images
por: Rao, B. Nageswara, et al.
Publicado: (2022) -
Fusion of Higher Order Spectra and Texture Extraction Methods for Automated Stroke Severity Classification with MRI Images
por: Faust, Oliver, et al.
Publicado: (2021) -
Explainable Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Machine Learning Techniques in a Population of 1780 Patients
por: Oei, Chien Wei, et al.
Publicado: (2023) -
Application of Artificial Intelligence Techniques for Monkeypox: A Systematic Review
por: Chadaga, Krishnaraj, et al.
Publicado: (2023) -
Prognosis of ischemic stroke predicted by machine learning based on multi-modal MRI radiomics
por: Yu, Huan, et al.
Publicado: (2023)