Multiscale-based multimodal image classification of brain tumor using deep learning method

R Rajasree, CC Columbus, C Shilaja - Neural Computing and Applications, 2021 - Springer
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 …

[HTML][HTML] A deep learning approach for brain tumor classification and segmentation using a multiscale convolutional neural network

FJ Díaz-Pernas, M Martínez-Zarzuela… - Healthcare, 2021 - mdpi.com
… 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 …

[HTML][HTML] Multiscale modeling reveals angiogenesis-induced drug resistance in brain tumors and predicts a synergistic drug combination targeting EGFR and VEGFR …

W Liang, Y Zheng, J Zhang, X Sun - BMC bioinformatics, 2019 - Springer
… cells to drug treatment has rarely been mechanistically studied. Therefore, a multiscale
model is required to investigate such complex biological systems that contain interactions and …

Colloquium: Multiscale modeling of brain network organization

C Presigny, F De Vico Fallani - Reviews of Modern Physics, 2022 - APS
… 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 …

Aggregating multi-scale prediction based on 3D U-Net in brain tumor segmentation

M Chen, Y Wu, J Wu - … Stroke and Traumatic Brain Injuries: 5th International …, 2020 - Springer
… 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…

Deep multi-scale 3D convolutional neural network (CNN) for MRI gliomas brain tumor classification

H Mzoughi, I Njeh, A Wali, MB Slima… - … of Digital Imaging, 2020 - Springer
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

Integrated biophysical modeling and image analysis: application to neuro-oncology

A Mang, S Bakas, S Subramanian… - Annual review of …, 2020 - annualreviews.org
… for characterization of neuroimaging data of brain tumor patients. We have … studies have
provided evidence of noninvasive comprehensive multiscale characterization of a tumor's

[HTML][HTML] Multi-scale segmentation in GBM treatment using diffusion tensor imaging

R Rahmat, K Saednia, MRHH Khani, M Rahmati… - Computers in biology …, 2020 - Elsevier
… 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 …

[HTML][HTML] Multiscale imaging approach for studying the central nervous system: methodology and perspective

M Fratini, A Abdollahzadeh, M DiNuzzo… - Frontiers in …, 2020 - frontiersin.org
… A multiscale and multidisciplinary approach as proposed in this article paves new ways
to study the brain and spinal cord, and more importantly, to better understand the non-invasive …

[HTML][HTML] Deep convolutional neural network with a multi-scale attention feature fusion module for segmentation of multimodal brain tumor

X He, W Xu, J Yang, J Mao, S Chen… - Frontiers in Neuroscience, 2021 - frontiersin.org
images are utilized as a data carrier to study the segmentation of glioma, which has the
greatest risk of malignancies in brain tumorsbrain tumors, many researchers have studied the …