Advancements in brain tumor analysis: a comprehensive review of machine learning, hybrid deep learning, and transfer learning approaches for MRI-based …
S Das, RS Goswami - Multimedia Tools and Applications, 2024 - Springer
Brain tumors, whether cancerous or noncancerous, can be life-threatening due to abnormal
cell growth, potentially causing organ dysfunction and mortality in adults. Brain tumor …
cell growth, potentially causing organ dysfunction and mortality in adults. Brain tumor …
Deep learning and optimized learning machine for brain tumor classification
B Sandhiya, SKS Raja - Biomedical Signal Processing and Control, 2024 - Elsevier
Brain Tumor classification in MRI images is a time-consuming and tedious task for medical
professionals. An accurate classification model can assist healthcare providers in treating …
professionals. An accurate classification model can assist healthcare providers in treating …
Integration of graph network with kernel SVM and logistic regression for identification of biomarkers in SCA12 and its diagnosis
Spinocerebellar ataxia type 12 is a hereditary and neurodegenerative illness commonly
found in India. However, there is no established noninvasive automatic diagnostic system for …
found in India. However, there is no established noninvasive automatic diagnostic system for …
Real-time GB pattern convolution neural network-based brain image classification
AR Panyala, M Baskar - AIP Conference Proceedings, 2024 - pubs.aip.org
Medical image classification has been identified as a critical task in several medical
solutions. Brain image classification has been identified as a challenging task that has been …
solutions. Brain image classification has been identified as a challenging task that has been …
An Efficient Classification Techniques for Brain Tumor Using Features Extraction and Statistic Methods, with Machine Learning Algorithms
Today, brain tumor is a very dangerous disease that can even cause death. There are many
ways to classify Brain MRI images of tumors. Various aspects of current research have …
ways to classify Brain MRI images of tumors. Various aspects of current research have …
Deep and hand-crafted features based on Weierstrass elliptic function for MRI brain tumor classification
Advances in medical imaging and artificial intelligence have led to improvements in
diagnosis and non-invasive patient examination accuracy. The use of the fundamental …
diagnosis and non-invasive patient examination accuracy. The use of the fundamental …
Review of Transfer Learning Techniques for MRI-based Brain Tumor Image Segmentation
Transfer learning (TL) techniques are used to segment brain tumor (BT) images using
magnetic resonance imaging (MRI) as our approach. Our goal is to generate well …
magnetic resonance imaging (MRI) as our approach. Our goal is to generate well …
Noise Estimation for MRI Images with Revised Theory on Histograms of Second-order Derivatives
WT Chan - International Journal on Robotics, Automation and …, 2023 - mmupress.com
Previous research by the author in the use of histograms of second-order derivatives
showed that the differences between pixels in MRI images can be determined without …
showed that the differences between pixels in MRI images can be determined without …
PRCnet: An Efficient Model for Automatic Detection of Brain Tumor in MRI Images
Brain tumors are the most prevalent and life-threatening cancer; an early and accurate
diagnosis of brain tumors increases the chances of patient survival and treatment planning …
diagnosis of brain tumors increases the chances of patient survival and treatment planning …
Optimization of IoT Devices in Smart Home to Minimize Cost Energy
Smart home systems are becoming an exciting new paradigm among researchers and
homeowners. In modern society, the use of electrical appliances is an essential element for …
homeowners. In modern society, the use of electrical appliances is an essential element for …