… brain image analysis. MRI [1] is the popular method used in diagnosing and analyzing
the brain tumor. Manual … In CNN [8] research, many researchers have proposed high-performance …

… T1-CE images highlight tumor borders and FLAIR images … of MRI image processing is to
locate and classify brain tumors, T1-… Most of the recent brain tumor classification studies using …

… II, we illustrate the rationale of multiscale brain modeling and review the main research
lines and challenges. These arguments allow the introduction of multilayer network theory to …

… imaging analysis for full assistance of neuroradiology during clinical diagnosis. We propose,
in this paper, an efficient and fully automatic deep multi-scale three-… The principal research …

… for characterization of neuroimaging data of brain tumor patients. We have … studies have
provided evidence of noninvasive comprehensive multiscale characterization of a tumor's …

… can be further used in other research (eg tumor size calculation, tumor shape analysis, …
aggregates multi-scale predictions from the decoder part of 3D U-Net in brain tumor segmentation…

… Our research work to date confirms the clinical utility of p and q maps for the assessment of
… a researcher with > 4 years of brain tumor image analysis experience (NRB). Segmentations …

… images are utilized as a data carrier to study the segmentation of glioma, which has the
greatest risk of malignancies in brain tumors… brain tumors, many researchers have studied the …

… Glioblastoma multiforme (GBM) is the most aggressive and malignant type of brain tumor [1]…
reliable in vitro models for cell studies by recapitulating some native properties of the brain’s …

… medical image analysis for … study develops an efficient network for brain tumor segmentation.
Specifically, dilated convolution is used to obtain multiscale receptive fields, and multiscale …