Quantitative imaging of apoptosis following oncolytic virotherapy by magnetic resonance fingerprinting aided by deep learning
Non-invasive imaging methods for detecting intratumoural viral spread and host responses
to oncolytic virotherapy are either slow, lack specificity or require the use of radioactive or …
to oncolytic virotherapy are either slow, lack specificity or require the use of radioactive or …
HWOA: A hybrid whale optimization algorithm with a novel local minima avoidance method for multi-level thresholding color image segmentation
M Abdel-Basset, R Mohamed, NM AbdelAziz… - Expert Systems with …, 2022 - Elsevier
Traditional methods to address color image segmentation work efficiently for bi-level
thresholding. However, for multi-level thresholding, traditional methods suffer from time …
thresholding. However, for multi-level thresholding, traditional methods suffer from time …
A novel beta differential evolution algorithm-based fast multilevel thresholding for color image segmentation
AK Bhandari - Neural computing and applications, 2020 - Springer
Multilevel thresholding for image segmentation is a crucial process in several applications
such as feature extraction and pattern recognition. The meticulous search for the best values …
such as feature extraction and pattern recognition. The meticulous search for the best values …
Use of machine intelligence to conduct analysis of human brain data for detection of abnormalities in its cognitive functions
The physical appearance of a brain tumor in human beings may be an indication of
problems in psychological (cognitive) functions. Such functions include learning …
problems in psychological (cognitive) functions. Such functions include learning …
Detection of dendritic spines using wavelet packet entropy and fuzzy support vector machine
The morphology of dendritic spines is highly correlated with the neuron function. Therefore,
it is of positive influence for the research of the dendritic spines. However, it is tried to …
it is of positive influence for the research of the dendritic spines. However, it is tried to …
Deep radiomics for brain tumor detection and classification from multi-sequence MRI
Glioma constitutes 80% of malignant primary brain tumors and is usually classified as HGG
and LGG. The LGG tumors are less aggressive, with slower growth rate as compared to …
and LGG. The LGG tumors are less aggressive, with slower growth rate as compared to …
Hybrid segmentation method with confidence region detection for tumor identification
Segmentation methods can mutually exclude the location of the tumor. However, the
challenge of complex location or incomplete identification is located in segmentation …
challenge of complex location or incomplete identification is located in segmentation …
Review on hybrid segmentation methods for identification of brain tumor in MRI
Modalities like MRI give information about organs and highlight diseases. Organ information
is visualized in intensities. The segmentation method plays an important role in the …
is visualized in intensities. The segmentation method plays an important role in the …
Deep learning with radiogenomics towards personalized management of gliomas
S Mitra - IEEE Reviews in Biomedical Engineering, 2021 - ieeexplore.ieee.org
A state-of-the-art interdisciplinary survey on multi-modal radiogenomic approaches is
presented involving applications to the diagnosis and personalized management of gliomas …
presented involving applications to the diagnosis and personalized management of gliomas …
[HTML][HTML] Brain tumor segmentation from multi-modal MR images via ensembling UNets
Glioma is a type of severe brain tumor, and its accurate segmentation is useful in surgery
planning and progression evaluation. Based on different biological properties, the glioma …
planning and progression evaluation. Based on different biological properties, the glioma …