Brain tumor segmentation of MRI images: A comprehensive review on the application of artificial intelligence tools
Background Brain cancer is a destructive and life-threatening disease that imposes
immense negative effects on patients' lives. Therefore, the detection of brain tumors at an …
immense negative effects on patients' lives. Therefore, the detection of brain tumors at an …
[HTML][HTML] Deep learning for smart Healthcare—A survey on brain tumor detection from medical imaging
M Arabahmadi, R Farahbakhsh, J Rezazadeh - Sensors, 2022 - mdpi.com
Advances in technology have been able to affect all aspects of human life. For example, the
use of technology in medicine has made significant contributions to human society. In this …
use of technology in medicine has made significant contributions to human society. In this …
[HTML][HTML] Brain tumor analysis using deep learning and VGG-16 ensembling learning approaches
A brain tumor is a distorted tissue wherein cells replicate rapidly and indefinitely, with no
control over tumor growth. Deep learning has been argued to have the potential to …
control over tumor growth. Deep learning has been argued to have the potential to …
Brain tumor segmentation and grading of lower-grade glioma using deep learning in MRI images
Gliomas are the most common malignant brain tumors with different grades that highly
determine the rate of survival in patients. Tumor segmentation and grading using magnetic …
determine the rate of survival in patients. Tumor segmentation and grading using magnetic …
[HTML][HTML] Medical image analysis based on deep learning approach
M Puttagunta, S Ravi - Multimedia tools and applications, 2021 - Springer
Medical imaging plays a significant role in different clinical applications such as medical
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …
An artificial intelligence framework and its bias for brain tumor segmentation: A narrative review
Background Artificial intelligence (AI) has become a prominent technique for medical
diagnosis and represents an essential role in detecting brain tumors. Although AI-based …
diagnosis and represents an essential role in detecting brain tumors. Although AI-based …
Machine learning for medical imaging
Machine learning is a technique for recognizing patterns that can be applied to medical
images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be …
images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be …
[HTML][HTML] Deep learning for brain MRI segmentation: state of the art and future directions
Quantitative analysis of brain MRI is routine for many neurological diseases and conditions
and relies on accurate segmentation of structures of interest. Deep learning-based …
and relies on accurate segmentation of structures of interest. Deep learning-based …
Automatic brain tumor detection and segmentation using U-Net based fully convolutional networks
A major challenge in brain tumor treatment planning and quantitative evaluation is
determination of the tumor extent. The noninvasive magnetic resonance imaging (MRI) …
determination of the tumor extent. The noninvasive magnetic resonance imaging (MRI) …
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 …