[HTML][HTML] Accurate prediction of glioma grades from radiomics using a multi-filter and multi-objective-based method
Radiomics, providing quantitative data extracted from medical images, has emerged as a
critical role in diagnosis and classification of diseases such as glioma. One main challenge …
critical role in diagnosis and classification of diseases such as glioma. One main challenge …
Expert knowledge guided manifold representation learning for magnetic resonance imaging-based glioma grading
Radiomics and deep learning have shown high popularity in automatic glioma grading.
Radiomics extracts handcrafted features that quantitatively describe the expert knowledge of …
Radiomics extracts handcrafted features that quantitatively describe the expert knowledge of …
Développement de modèles interprétables par des approches d'apprentissage à partir d'images TEP, TDM, et IRM pour la prise en charge de patients atteints de …
T Escobar - 2023 - theses.hal.science
Cette thèse en partenariat avec l'Institut Curie et la société DOSIsoft explore l'importance
croissante des sciences numériques en santé, en particulier dans le domaine de l'imagerie …
croissante des sciences numériques en santé, en particulier dans le domaine de l'imagerie …
Automated Grading of Glioma Using Deep Neural Networks
Gliomas are one of the most common tumors in the brain. It is possible to grade gliomas as
Lower-Grade Glioma (LGG) and Glioblastoma Multiforme (GBM). Clinical and …
Lower-Grade Glioma (LGG) and Glioblastoma Multiforme (GBM). Clinical and …