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Deep learning for smart Healthcare—A survey on brain tumor detection from medical imaging
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 …
Brain tumor segmentation and classification from magnetic resonance images: Review of selected methods from 2014 to 2019
The past few years have witnessed a significant increase in medical cases related to brain
tumors, making it the 10th most common form of tumor affecting children and adults alike …
tumors, making it the 10th most common form of tumor affecting children and adults alike …
Edge U-Net: Brain tumor segmentation using MRI based on deep U-Net model with boundary information
Blood clots in the brain are frequently caused by brain tumors. Early detection of these clots
has the potential to significantly lower morbidity and mortality in cases of brain cancer. It is …
has the potential to significantly lower morbidity and mortality in cases of brain cancer. It is …
[HTML][HTML] A survey of brain tumor segmentation and classification algorithms
A brain Magnetic resonance imaging (MRI) scan of a single individual consists of several
slices across the 3D anatomical view. Therefore, manual segmentation of brain tumors from …
slices across the 3D anatomical view. Therefore, manual segmentation of brain tumors from …
A review on brain tumor segmentation of MRI images
The process of segmenting tumor from MRI image of a brain is one of the highly focused
areas in the community of medical science as MRI is noninvasive imaging. This paper …
areas in the community of medical science as MRI is noninvasive imaging. This paper …
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 …
A review on brain tumor diagnosis from MRI images: Practical implications, key achievements, and lessons learned
The successful early diagnosis of brain tumors plays a major role in improving the treatment
outcomes and thus improving patient survival. Manually evaluating the numerous magnetic …
outcomes and thus improving patient survival. Manually evaluating the numerous magnetic …
[HTML][HTML] Using U-Net network for efficient brain tumor segmentation in MRI images
Abstract Magnetic Resonance Imaging (MRI) is the most commonly used non-intrusive
technique for medical image acquisition. Brain tumor segmentation is the process of …
technique for medical image acquisition. Brain tumor segmentation is the process of …
[Retracted] Brain Tumor Detection and Classification by MRI Using Biologically Inspired Orthogonal Wavelet Transform and Deep Learning Techniques
Radiology is a broad subject that needs more knowledge and understanding of medical
science to identify tumors accurately. The need for a tumor detection program, thus …
science to identify tumors accurately. The need for a tumor detection program, thus …
Image analysis for MRI based brain tumor detection and feature extraction using biologically inspired BWT and SVM
The segmentation, detection, and extraction of infected tumor area from magnetic resonance
(MR) images are a primary concern but a tedious and time taking task performed by …
(MR) images are a primary concern but a tedious and time taking task performed by …