Brain tumor detection and classification using machine learning: a comprehensive survey
J Amin, M Sharif, A Haldorai, M Yasmin… - Complex & intelligent …, 2022 - Springer
Brain tumor occurs owing to uncontrolled and rapid growth of cells. If not treated at an initial
phase, it may lead to death. Despite many significant efforts and promising outcomes in this …
phase, it may lead to death. Despite many significant efforts and promising outcomes in this …
Brain tumor analysis empowered with deep learning: A review, taxonomy, and future challenges
Deep Learning (DL) algorithms enabled computational models consist of multiple
processing layers that represent data with multiple levels of abstraction. In recent years …
processing layers that represent data with multiple levels of abstraction. In recent years …
Brain tumor detection using fusion of hand crafted and deep learning features
T Saba, AS Mohamed, M El-Affendi, J Amin… - Cognitive Systems …, 2020 - Elsevier
The perilous disease in the worldwide now a days is brain tumor. Tumor affects the brain by
damaging healthy tissues or intensifying intra cranial pressure. Hence, rapid growth in tumor …
damaging healthy tissues or intensifying intra cranial pressure. Hence, rapid growth in tumor …
Advancing the cancer genome atlas glioma MRI collections with expert segmentation labels and radiomic features
Gliomas belong to a group of central nervous system tumors, and consist of various sub-
regions. Gold standard labeling of these sub-regions in radiographic imaging is essential for …
regions. Gold standard labeling of these sub-regions in radiographic imaging is essential for …
A deep learning model integrating FCNNs and CRFs for brain tumor segmentation
Accurate and reliable brain tumor segmentation is a critical component in cancer diagnosis,
treatment planning, and treatment outcome evaluation. Build upon successful deep learning …
treatment planning, and treatment outcome evaluation. Build upon successful deep learning …
Brain tumor classification based on DWT fusion of MRI sequences using convolutional neural network
Tumor in brain is an anthology of anomalous cells. It leads to increase in death rate among
humans. Therefore, in this manuscript, a fusion process is proposed to combine structural …
humans. Therefore, in this manuscript, a fusion process is proposed to combine structural …
Decentralized federated learning for healthcare networks: A case study on tumor segmentation
Smart healthcare relies on artificial intelligence (AI) functions for learning and analysis of
patient data. Since large and diverse datasets for training of Machine Learning (ML) models …
patient data. Since large and diverse datasets for training of Machine Learning (ML) models …
Brain tumor detection: a long short-term memory (LSTM)-based learning model
To overcome the problems of automated brain tumor classification, a novel approach is
proposed based on long short-term memory (LSTM) model using magnetic resonance …
proposed based on long short-term memory (LSTM) model using magnetic resonance …
Enhanced region growing for brain tumor MR image segmentation
ES Biratu, F Schwenker, TG Debelee, SR Kebede… - Journal of …, 2021 - mdpi.com
A brain tumor is one of the foremost reasons for the rise in mortality among children and
adults. A brain tumor is a mass of tissue that propagates out of control of the normal forces …
adults. A brain tumor is a mass of tissue that propagates out of control of the normal forces …
Brain tumor detection by using stacked autoencoders in deep learning
Brain tumor detection depicts a tough job because of its shape, size and appearance
variations. In this manuscript, a deep learning model is deployed to predict input slices as a …
variations. In this manuscript, a deep learning model is deployed to predict input slices as a …