A review on a deep learning perspective in brain cancer classification
A World Health Organization (WHO) Feb 2018 report has recently shown that mortality rate
due to brain or central nervous system (CNS) cancer is the highest in the Asian continent. It …
due to brain or central nervous system (CNS) cancer is the highest in the Asian continent. It …
Radiomics: a new application from established techniques
The increasing use of biomarkers in cancer have led to the concept of personalized
medicine for patients. Personalized medicine provides better diagnosis and treatment …
medicine for patients. Personalized medicine provides better diagnosis and treatment …
Deep-learning convolutional neural networks accurately classify genetic mutations in gliomas
P Chang, J Grinband, BD Weinberg… - American Journal …, 2018 - Am Soc Neuroradiology
BACKGROUND AND PURPOSE: The World Health Organization has recently placed new
emphasis on the integration of genetic information for gliomas. While tissue sampling …
emphasis on the integration of genetic information for gliomas. While tissue sampling …
Radiomic features from the peritumoral brain parenchyma on treatment-naive multi-parametric MR imaging predict long versus short-term survival in glioblastoma …
Objective Despite 90% of glioblastoma (GBM) recurrences occurring in the peritumoral brain
zone (PBZ), its contribution in patient survival is poorly understood. The current study …
zone (PBZ), its contribution in patient survival is poorly understood. The current study …
Performance optimisation of deep learning models using majority voting algorithm for brain tumour classification
Background Although biopsy is the gold standard for tumour grading, being invasive, this
procedure also proves fatal to the brain. Thus, non-invasive methods for brain tumour …
procedure also proves fatal to the brain. Thus, non-invasive methods for brain tumour …
Gray-level invariant Haralick texture features
Haralick texture features are common texture descriptors in image analysis. To compute the
Haralick features, the image gray-levels are reduced, a process called quantization. The …
Haralick features, the image gray-levels are reduced, a process called quantization. The …
Radiomics strategy for glioma grading using texture features from multiparametric MRI
Q Tian, LF Yan, X Zhang, X Zhang… - Journal of Magnetic …, 2018 - Wiley Online Library
Background Accurate glioma grading plays an important role in the clinical management of
patients and is also the basis of molecular stratification nowadays. Purpose/Hypothesis To …
patients and is also the basis of molecular stratification nowadays. Purpose/Hypothesis To …
Classification of the glioma grading using radiomics analysis
Background Grading of gliomas is critical information related to prognosis and survival. We
aimed to apply a radiomics approach using various machine learning classifiers to …
aimed to apply a radiomics approach using various machine learning classifiers to …
[HTML][HTML] The link between diffusion MRI and tumor heterogeneity: Mapping cell eccentricity and density by diffusional variance decomposition (DIVIDE)
F Szczepankiewicz, D van Westen, E Englund… - Neuroimage, 2016 - Elsevier
The structural heterogeneity of tumor tissue can be probed by diffusion MRI (dMRI) in terms
of the variance of apparent diffusivities within a voxel. However, the link between the …
of the variance of apparent diffusivities within a voxel. However, the link between the …
Haralick texture features from apparent diffusion coefficient (ADC) MRI images depend on imaging and pre-processing parameters
P Brynolfsson, D Nilsson, T Torheim, T Asklund… - Scientific reports, 2017 - nature.com
In recent years, texture analysis of medical images has become increasingly popular in
studies investigating diagnosis, classification and treatment response assessment of …
studies investigating diagnosis, classification and treatment response assessment of …