Machine-Learning-Based Radiomics for Classifying Glioma Grade from Magnetic Resonance Images of the Brain

Grading of gliomas is a piece of critical information related to prognosis and survival. Classifying glioma grade by semantic radiological features is subjective, requires multiple MRI sequences, is quite complex and clinically demanding, and can very often result in erroneous radiological diagnosis...

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Detalles Bibliográficos
Autores principales: Kumar, Anuj, Jha, Ashish Kumar, Agarwal, Jai Prakash, Yadav, Manender, Badhe, Suvarna, Sahay, Ayushi, Epari, Sridhar, Sahu, Arpita, Bhattacharya, Kajari, Chatterjee, Abhishek, Ganeshan, Balaji, Rangarajan, Venkatesh, Moyiadi, Aliasgar, Gupta, Tejpal, Goda, Jayant S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10305272/
https://www.ncbi.nlm.nih.gov/pubmed/37373909
http://dx.doi.org/10.3390/jpm13060920

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10305272/
https://www.ncbi.nlm.nih.gov/pubmed/37373909
http://dx.doi.org/10.3390/jpm13060920

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