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[HTML][HTML] A review of uncertainty quantification in deep learning: Techniques, applications and challenges
Uncertainty quantification (UQ) methods play a pivotal role in reducing the impact of
uncertainties during both optimization and decision making processes. They have been …
uncertainties during both optimization and decision making processes. They have been …
Data augmentation for brain-tumor segmentation: a review
Data augmentation is a popular technique which helps improve generalization capabilities
of deep neural networks, and can be perceived as implicit regularization. It plays a pivotal …
of deep neural networks, and can be perceived as implicit regularization. It plays a pivotal …
A survey of uncertainty in deep neural networks
Over the last decade, neural networks have reached almost every field of science and
become a crucial part of various real world applications. Due to the increasing spread …
become a crucial part of various real world applications. Due to the increasing spread …
Deep transfer learning approaches in performance analysis of brain tumor classification using MRI images
Brain tumor classification is a very important and the most prominent step for assessing life‐
threatening abnormal tissues and providing an efficient treatment in patient recovery. To …
threatening abnormal tissues and providing an efficient treatment in patient recovery. To …
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
Gliomas are the most common primary brain malignancies, with different degrees of
aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, ie …
aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, ie …
Attention gate resU-Net for automatic MRI brain tumor segmentation
Brain tumor segmentation technology plays a pivotal role in the process of diagnosis and
treatment of MRI brain tumors. It helps doctors to locate and measure tumors, as well as …
treatment of MRI brain tumors. It helps doctors to locate and measure tumors, as well as …
U-Net-based models towards optimal MR brain image segmentation
Brain tumor segmentation from MRIs has always been a challenging task for radiologists,
therefore, an automatic and generalized system to address this task is needed. Among all …
therefore, an automatic and generalized system to address this task is needed. Among all …
Automatic brain tumor segmentation based on cascaded convolutional neural networks with uncertainty estimation
Automatic segmentation of brain tumors from medical images is important for clinical
assessment and treatment planning of brain tumors. Recent years have seen an increasing …
assessment and treatment planning of brain tumors. Recent years have seen an increasing …
Brain tumor detection and multi-grade segmentation through hybrid caps-VGGNet model
Around the world, brain tumors are becoming the leading cause of mortality. The inability to
undertake a timely tumor diagnosis is the primary cause of this pandemic. Brain cancer …
undertake a timely tumor diagnosis is the primary cause of this pandemic. Brain cancer …
RAAGR2-Net: A brain tumor segmentation network using parallel processing of multiple spatial frames
Brain tumors are one of the most fatal cancers. Magnetic Resonance Imaging (MRI) is a non-
invasive method that provides multi-modal images containing important information …
invasive method that provides multi-modal images containing important information …