Brain tumor detection and classification using intelligence techniques: an overview
S Solanki, UP Singh, SS Chouhan, S Jain - IEEE Access, 2023 - ieeexplore.ieee.org
A tumor is carried on by rapid and uncontrolled cell growth in the brain. If it is not treated in
the initial phases, it could prove fatal. Despite numerous significant efforts and encouraging …
the initial phases, it could prove fatal. Despite numerous significant efforts and encouraging …
Artificial intelligence in brain tumor detection through MRI scans: advancements and challenges
A brain tumor is one of the most perilous diseases in human beings. The manual
segmentation of brain tumors is costly and takes a lot of time; due to this reason, automated …
segmentation of brain tumors is costly and takes a lot of time; due to this reason, automated …
An enhanced deep learning approach for brain cancer MRI images classification using residual networks
Cancer is the second leading cause of death after cardiovascular diseases. Out of all types
of cancer, brain cancer has the lowest survival rate. Brain tumors can have different types …
of cancer, brain cancer has the lowest survival rate. Brain tumors can have different types …
Early diagnosis of brain tumour mri images using hybrid techniques between deep and machine learning
Cancer is considered one of the most aggressive and destructive diseases that shortens the
average lives of patients. Misdiagnosed brain tumours lead to false medical intervention …
average lives of patients. Misdiagnosed brain tumours lead to false medical intervention …
An enhanced deep learning method for multi-class brain tumor classification using deep transfer learning
Multi-class brain tumor classification is an important area of research in the field of medical
imaging because of the different tumor characteristics. One such challenging problem is the …
imaging because of the different tumor characteristics. One such challenging problem is the …
Vox2Vox: 3D-GAN for brain tumour segmentation
Gliomas are the most common primary brain malignancies, with different degrees of
aggressiveness, variable prognosis and various heterogeneous histological sub-regions, ie …
aggressiveness, variable prognosis and various heterogeneous histological sub-regions, ie …
A survey of deep learning for MRI brain tumor segmentation methods: Trends, challenges, and future directions
S Krishnapriya, Y Karuna - Health and Technology, 2023 - Springer
Abstract Purpose Structural Magnetic Resonance Imaging (MRI) of the brain is an effective
way to study its internal structure. Identifying and classifying brain malignancies is a difficult …
way to study its internal structure. Identifying and classifying brain malignancies is a difficult …
TumorDetNet: A unified deep learning model for brain tumor detection and classification
Accurate diagnosis of the brain tumor type at an earlier stage is crucial for the treatment
process and helps to save the lives of a large number of people worldwide. Because they …
process and helps to save the lives of a large number of people worldwide. Because they …
[HTML][HTML] Applications of artificial intelligence in nuclear medicine image generation
Z Cheng, J Wen, G Huang, J Yan - Quantitative Imaging in …, 2021 - ncbi.nlm.nih.gov
Recently, the application of artificial intelligence (AI) in medical imaging (including nuclear
medicine imaging) has rapidly developed. Most AI applications in nuclear medicine imaging …
medicine imaging) has rapidly developed. Most AI applications in nuclear medicine imaging …
Exploring the power of deep learning: fine-tuned vision transformer for accurate and efficient brain tumor detection in MRI scans
A brain tumor is a significant health concern that directly or indirectly affects thousands of
people worldwide. The early and accurate detection of brain tumors is vital to the successful …
people worldwide. The early and accurate detection of brain tumors is vital to the successful …