12 citations · 17 across the 3 of their papers we have counts for
3 papers
Deep Learning for Reaction-Diffusion Glioma Growth Modelling: Towards a Fully Personalised Model?
Corentin Martens, Antonin Rovai, Daniele Bonatto +5
Reaction-diffusion models have been proposed for decades to capture the growth of gliomas, the most common primary brain tumours. However, severe limitations regarding the estimati…
Initial condition assessment for reaction-diffusion glioma growth models: A translational MRI/histology (in)validation study
Corentin Martens, Laetitia Lebrun, Christine Decaestecker +8
Diffuse gliomas are highly infiltrative tumors whose early diagnosis and follow-up usually rely on magnetic resonance imaging (MRI). However, the limited sensitivity of this techni…
Voxelwise principal component analysis of dynamic [S-methyl-11C]methionine PET data in glioma patients
Corentin Martens, Olivier Debeir, Christine Decaestecker +6
Recent works have demonstrated the added value of dynamic amino acid positron emission tomography (PET) for glioma grading and genotyping, biopsy targeting, and recurrence diagnosi…